"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pos_df = pd.DataFrame(train_features[ bool_train_labels], columns=train_df.columns)\n",
"neg_df = pd.DataFrame(train_features[~bool_train_labels], columns=train_df.columns)\n",
"\n",
"sns.jointplot(x=pos_df['V5'], y=pos_df['V6'],\n",
" kind='hex', xlim=(-5,5), ylim=(-5,5))\n",
"plt.suptitle(\"Positive distribution\")\n",
"\n",
"sns.jointplot(x=neg_df['V5'], y=neg_df['V6'],\n",
" kind='hex', xlim=(-5,5), ylim=(-5,5))\n",
"_ = plt.suptitle(\"Negative distribution\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "qFK1u4JX16D8"
},
"source": [
"## Define the model and metrics\n",
"\n",
"Define a function that creates a simple neural network with a densly connected hidden layer, a [dropout](https://developers.google.com/machine-learning/glossary/#dropout_regularization) layer to reduce overfitting, and an output sigmoid layer that returns the probability of a transaction being fraudulent:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:24:00.630075Z",
"iopub.status.busy": "2024-08-20T01:24:00.629439Z",
"iopub.status.idle": "2024-08-20T01:24:02.924576Z",
"shell.execute_reply": "2024-08-20T01:24:02.923896Z"
},
"id": "3JQDzUqT3UYG"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
"I0000 00:00:1724117041.170464 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.173954 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.177520 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.181109 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.192229 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.195501 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.198855 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.202289 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.205917 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.209120 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.212551 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117041.215957 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.481641 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.483772 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.485797 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.487790 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.489919 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.491898 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.493821 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.495734 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.497770 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.499729 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.501678 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.503579 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.543692 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.545712 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.547685 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.549729 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.551904 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.553845 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.555812 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.557712 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.559788 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.563396 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.565786 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
"I0000 00:00:1724117042.568056 9349 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n"
]
}
],
"source": [
"METRICS = [\n",
" keras.metrics.BinaryCrossentropy(name='cross entropy'), # same as model's loss\n",
" keras.metrics.MeanSquaredError(name='Brier score'),\n",
" keras.metrics.TruePositives(name='tp'),\n",
" keras.metrics.FalsePositives(name='fp'),\n",
" keras.metrics.TrueNegatives(name='tn'),\n",
" keras.metrics.FalseNegatives(name='fn'),\n",
" keras.metrics.BinaryAccuracy(name='accuracy'),\n",
" keras.metrics.Precision(name='precision'),\n",
" keras.metrics.Recall(name='recall'),\n",
" keras.metrics.AUC(name='auc'),\n",
" keras.metrics.AUC(name='prc', curve='PR'), # precision-recall curve\n",
"]\n",
"\n",
"def make_model(metrics=METRICS, output_bias=None):\n",
" if output_bias is not None:\n",
" output_bias = tf.keras.initializers.Constant(output_bias)\n",
" model = keras.Sequential([\n",
" keras.layers.Dense(\n",
" 16, activation='relu',\n",
" input_shape=(train_features.shape[-1],)),\n",
" keras.layers.Dropout(0.5),\n",
" keras.layers.Dense(1, activation='sigmoid',\n",
" bias_initializer=output_bias),\n",
" ])\n",
"\n",
" model.compile(\n",
" optimizer=keras.optimizers.Adam(learning_rate=1e-3),\n",
" loss=keras.losses.BinaryCrossentropy(),\n",
" metrics=metrics)\n",
"\n",
" return model"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "SU0GX6E6mieP"
},
"source": [
"### Understanding useful metrics\n",
"\n",
"Notice that there are a few metrics defined above that can be computed by the model that will be helpful when evaluating the performance.\n",
"These can be divided into three groups.\n",
"\n",
"#### Metrics for probability predictions\n",
"\n",
"As we train our network with the cross entropy as a loss function, it is fully capable of predicting class probabilities, i.e., it is a probabilistic classifier.\n",
"Good metrics to assess probabilistic predictions are, in fact, **proper scoring rules**. Their key property is that predicting the true probability is optimal. We give two well-known examples:\n",
"\n",
"* **cross entropy** also known as log loss\n",
"* **Mean squared error** also known as the Brier score\n",
"\n",
"#### Metrics for deterministic 0/1 predictions\n",
"\n",
"In the end, one often wants to predict a class label, 0 or 1, *no fraud* or *fraud*.\n",
"This is called a deterministic classifier.\n",
"To get a label prediction from our probabilistic classifier, one needs to choose a probability threshold $t$.\n",
"The default is to predict label 1 (fraud) if the predicted probability is larger than $t=50\\%$ and all the following metrics implicitly use this default.\n",
"\n",
"* **False** negatives and **false** positives are samples that were **incorrectly** classified\n",
"* **True** negatives and **true** positives are samples that were **correctly** classified\n",
"* **Accuracy** is the percentage of examples correctly classified\n",
"> $\\frac{\\text{true samples}}{\\text{total samples}}$\n",
"* **Precision** is the percentage of **predicted** positives that were correctly classified\n",
"> $\\frac{\\text{true positives}}{\\text{true positives + false positives}}$\n",
"* **Recall** is the percentage of **actual** positives that were correctly classified\n",
"> $\\frac{\\text{true positives}}{\\text{true positives + false negatives}}$\n",
"\n",
"**Note:** Accuracy is not a helpful metric for this task. You can have 99.8%+ accuracy on this task by predicting False all the time. \n",
"\n",
"#### Other metrices\n",
"\n",
"The following metrics take into account all possible choices of thresholds $t$.\n",
"\n",
"* **AUC** refers to the Area Under the Curve of a Receiver Operating Characteristic curve (ROC-AUC). This metric is equal to the probability that a classifier will rank a random positive sample higher than a random negative sample.\n",
"* **AUPRC** refers to Area Under the Curve of the Precision-Recall Curve. This metric computes precision-recall pairs for different probability thresholds.\n",
"\n",
"\n",
"#### Read more:\n",
"* [Strictly Proper Scoring Rules, Prediction, and Estimation](https://www.stat.washington.edu/people/raftery/Research/PDF/Gneiting2007jasa.pdf)\n",
"* [True vs. False and Positive vs. Negative](https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative)\n",
"* [Accuracy](https://developers.google.com/machine-learning/crash-course/classification/accuracy)\n",
"* [Precision and Recall](https://developers.google.com/machine-learning/crash-course/classification/precision-and-recall)\n",
"* [ROC-AUC](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc)\n",
"* [Relationship between Precision-Recall and ROC Curves](https://www.biostat.wisc.edu/~page/rocpr.pdf)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "FYdhSAoaF_TK"
},
"source": [
"## Baseline model"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "IDbltVPg2m2q"
},
"source": [
"### Build the model\n",
"\n",
"Now create and train your model using the function that was defined earlier. Notice that the model is fit using a larger than default batch size of 2048, this is important to ensure that each batch has a decent chance of containing a few positive samples. If the batch size was too small, they would likely have no fraudulent transactions to learn from.\n",
"\n",
"\n",
"Note: Fitting this model will not handle the class imbalance efficiently. You will improve it later in this tutorial."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:24:02.928038Z",
"iopub.status.busy": "2024-08-20T01:24:02.927541Z",
"iopub.status.idle": "2024-08-20T01:24:02.931341Z",
"shell.execute_reply": "2024-08-20T01:24:02.930700Z"
},
"id": "ouUkwPcGQsy3"
},
"outputs": [],
"source": [
"EPOCHS = 100\n",
"BATCH_SIZE = 2048\n",
"\n",
"def early_stopping():\n",
" return tf.keras.callbacks.EarlyStopping(\n",
" monitor='val_prc',\n",
" verbose=1,\n",
" patience=10,\n",
" mode='max',\n",
" restore_best_weights=True)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:24:02.934380Z",
"iopub.status.busy": "2024-08-20T01:24:02.933837Z",
"iopub.status.idle": "2024-08-20T01:24:03.693014Z",
"shell.execute_reply": "2024-08-20T01:24:03.692190Z"
},
"id": "1xlR_dekzw7C"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
" super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
]
},
{
"data": {
"text/html": [
"Model: \"sequential\" \n",
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
"┃ Layer (type) ┃ Output Shape ┃ Param # ┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
"│ dense (Dense ) │ (None , 16 ) │ 480 │\n",
"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
"│ dropout (Dropout ) │ (None , 16 ) │ 0 │\n",
"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
"│ dense_1 (Dense ) │ (None , 1 ) │ 17 │\n",
"└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
" \n"
],
"text/plain": [
"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
"│ dense (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m) │ \u001b[38;5;34m480\u001b[0m │\n",
"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
"│ dropout (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n",
"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
"│ dense_1 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m17\u001b[0m │\n",
"└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" Total params: 497 (1.94 KB)\n",
" Trainable params: 497 (1.94 KB)\n",
" Non-trainable params: 0 (0.00 B)\n",
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_loss(zero_bias_history, \"Zero Bias\", 0)\n",
"plot_loss(careful_bias_history, \"Careful Bias\", 1)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "fKMioV0ddG3R"
},
"source": [
"The above figure makes it clear: In terms of validation loss, on this problem, this careful initialization gives a clear advantage."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "RsA_7SEntRaV"
},
"source": [
"### Train the model"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:24:40.603722Z",
"iopub.status.busy": "2024-08-20T01:24:40.603074Z",
"iopub.status.idle": "2024-08-20T01:25:08.457541Z",
"shell.execute_reply": "2024-08-20T01:25:08.456841Z"
},
"id": "yZKAc8NCDnoR"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5:00\u001b[0m 3s/step - Brier score: 4.8241e-04 - accuracy: 0.9995 - auc: 0.9423 - cross entropy: 0.0029 - fn: 20.0000 - fp: 5.0000 - loss: 0.0172 - prc: 0.8275 - precision: 0.9315 - recall: 0.7727 - tn: 47524.0000 - tp: 68.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m23/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.2044e-04 - accuracy: 0.9990 - auc: 0.8808 - cross entropy: 0.0058 - fn: 51.3478 - fp: 23.1739 - loss: 0.0134 - prc: 0.6085 - precision: 0.7575 - recall: 0.5881 - tn: 70002.4766 - tp: 68.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m48/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0011 - accuracy: 0.9987 - auc: 0.8472 - cross entropy: 0.0073 - fn: 92.5417 - fp: 36.7708 - loss: 0.0130 - prc: 0.4878 - precision: 0.6688 - recall: 0.4659 - tn: 95546.7500 - tp: 68.9375 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0012 - accuracy: 0.9986 - auc: 0.8305 - cross entropy: 0.0079 - fn: 131.0411 - fp: 45.4795 - loss: 0.0125 - prc: 0.4273 - precision: 0.6310 - recall: 0.4017 - tn: 121096.1953 - tp: 72.2877"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0013 - accuracy: 0.9986 - auc: 0.8239 - cross entropy: 0.0081 - fn: 157.4000 - fp: 49.8667 - loss: 0.0123 - prc: 0.4031 - precision: 0.6210 - recall: 0.3747 - tn: 138446.5938 - tp: 76.4222"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 44ms/step - Brier score: 0.0013 - accuracy: 0.9986 - auc: 0.8236 - cross entropy: 0.0082 - fn: 158.8681 - fp: 50.0989 - loss: 0.0123 - prc: 0.4019 - precision: 0.6206 - recall: 0.3733 - tn: 139423.9375 - tp: 76.6703 - val_Brier score: 0.0011 - val_accuracy: 0.9984 - val_auc: 0.9384 - val_cross entropy: 0.0054 - val_fn: 70.0000 - val_fp: 1.0000 - val_loss: 0.0054 - val_prc: 0.7641 - val_precision: 0.9231 - val_recall: 0.1463 - val_tn: 45486.0000 - val_tp: 12.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 55ms/step - Brier score: 1.0060e-04 - accuracy: 1.0000 - auc: 1.0000 - cross entropy: 0.0027 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 0.0027 - prc: 1.0000 - precision: 1.0000 - recall: 1.0000 - tn: 2047.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0011 - accuracy: 0.9989 - auc: 0.8707 - cross entropy: 0.0074 - fn: 27.1667 - fp: 3.9167 - loss: 0.0074 - prc: 0.5225 - precision: 0.8736 - recall: 0.4837 - tn: 25549.1660 - tp: 19.7500 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m48/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0011 - accuracy: 0.9989 - auc: 0.8722 - cross entropy: 0.0075 - fn: 51.9167 - fp: 8.6042 - loss: 0.0075 - prc: 0.4841 - precision: 0.8348 - recall: 0.4423 - tn: 50079.6445 - tp: 35.8333"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0011 - accuracy: 0.9989 - auc: 0.8716 - cross entropy: 0.0074 - fn: 76.9452 - fp: 12.6164 - loss: 0.0074 - prc: 0.4821 - precision: 0.8282 - recall: 0.4344 - tn: 75632.0000 - tp: 54.4384"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0011 - accuracy: 0.9988 - auc: 0.8707 - cross entropy: 0.0073 - fn: 96.2308 - fp: 15.1319 - loss: 0.0073 - prc: 0.4775 - precision: 0.8256 - recall: 0.4258 - tn: 93963.4297 - tp: 65.7802 - val_Brier score: 6.3164e-04 - val_accuracy: 0.9993 - val_auc: 0.9327 - val_cross entropy: 0.0039 - val_fn: 28.0000 - val_fp: 6.0000 - val_loss: 0.0039 - val_prc: 0.7800 - val_precision: 0.9000 - val_recall: 0.6585 - val_tn: 45481.0000 - val_tp: 54.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 1.6159e-05 - accuracy: 1.0000 - auc: 0.0000e+00 - cross entropy: 0.0017 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 0.0017 - prc: 0.0000e+00 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2048.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2879e-04 - accuracy: 0.9989 - auc: 0.8292 - cross entropy: 0.0052 - fn: 23.1667 - fp: 8.0417 - loss: 0.0052 - prc: 0.4518 - precision: 0.5768 - recall: 0.3527 - tn: 25554.2090 - tp: 14.5833 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m46/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.6755e-04 - accuracy: 0.9988 - auc: 0.8446 - cross entropy: 0.0061 - fn: 49.9130 - fp: 13.6522 - loss: 0.0061 - prc: 0.4499 - precision: 0.6282 - recall: 0.3528 - tn: 48036.2812 - tp: 28.1522"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m68/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0010 - accuracy: 0.9988 - auc: 0.8518 - cross entropy: 0.0063 - fn: 73.3971 - fp: 18.2206 - loss: 0.0063 - prc: 0.4544 - precision: 0.6598 - recall: 0.3599 - tn: 70521.5000 - tp: 42.8824 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0010 - accuracy: 0.9988 - auc: 0.8568 - cross entropy: 0.0064 - fn: 96.9670 - fp: 22.6703 - loss: 0.0064 - prc: 0.4659 - precision: 0.6843 - recall: 0.3704 - tn: 93960.5859 - tp: 60.3517 - val_Brier score: 5.2946e-04 - val_accuracy: 0.9994 - val_auc: 0.9327 - val_cross entropy: 0.0034 - val_fn: 22.0000 - val_fp: 7.0000 - val_loss: 0.0034 - val_prc: 0.8030 - val_precision: 0.8955 - val_recall: 0.7317 - val_tn: 45480.0000 - val_tp: 60.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 6.3397e-04 - accuracy: 0.9990 - auc: 0.9980 - cross entropy: 0.0037 - fn: 1.0000 - fp: 1.0000 - loss: 0.0037 - prc: 0.1074 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2046.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5081e-04 - accuracy: 0.9991 - auc: 0.9129 - cross entropy: 0.0047 - fn: 22.3846 - fp: 2.5000 - loss: 0.0047 - prc: 0.5223 - precision: 0.6904 - recall: 0.3075 - tn: 27608.1914 - tp: 14.9231 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0688e-04 - accuracy: 0.9990 - auc: 0.9220 - cross entropy: 0.0050 - fn: 45.3846 - fp: 8.5385 - loss: 0.0050 - prc: 0.5702 - precision: 0.7497 - recall: 0.3897 - tn: 54180.0586 - tp: 38.0192"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2630e-04 - accuracy: 0.9990 - auc: 0.9184 - cross entropy: 0.0052 - fn: 66.9744 - fp: 13.7949 - loss: 0.0052 - prc: 0.5836 - precision: 0.7727 - recall: 0.4258 - tn: 80753.4141 - tp: 61.8205"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 8.3760e-04 - accuracy: 0.9990 - auc: 0.9158 - cross entropy: 0.0052 - fn: 78.3736 - fp: 16.5714 - loss: 0.0052 - prc: 0.5847 - precision: 0.7786 - recall: 0.4360 - tn: 93971.8984 - tp: 73.7253 - val_Brier score: 5.1657e-04 - val_accuracy: 0.9994 - val_auc: 0.9328 - val_cross entropy: 0.0032 - val_fn: 20.0000 - val_fp: 7.0000 - val_loss: 0.0032 - val_prc: 0.8076 - val_precision: 0.8986 - val_recall: 0.7561 - val_tn: 45480.0000 - val_tp: 62.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 5/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 0.0016 - accuracy: 0.9980 - auc: 0.6592 - cross entropy: 0.0094 - fn: 3.0000 - fp: 1.0000 - loss: 0.0094 - prc: 0.1042 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2044.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0011 - accuracy: 0.9986 - auc: 0.8798 - cross entropy: 0.0064 - fn: 27.0000 - fp: 5.2917 - loss: 0.0064 - prc: 0.6326 - precision: 0.7874 - recall: 0.4486 - tn: 25542.5840 - tp: 25.1250 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.7706e-04 - accuracy: 0.9988 - auc: 0.8922 - cross entropy: 0.0058 - fn: 45.5319 - fp: 8.6596 - loss: 0.0058 - prc: 0.6538 - precision: 0.8140 - recall: 0.4738 - tn: 49053.1914 - tp: 44.6170"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m71/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.1842e-04 - accuracy: 0.9989 - auc: 0.8974 - cross entropy: 0.0055 - fn: 63.1831 - fp: 13.0845 - loss: 0.0055 - prc: 0.6589 - precision: 0.8180 - recall: 0.4868 - tn: 73587.4609 - tp: 64.2676"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 9.0654e-04 - accuracy: 0.9989 - auc: 0.8996 - cross entropy: 0.0054 - fn: 79.9890 - fp: 17.5714 - loss: 0.0054 - prc: 0.6563 - precision: 0.8161 - recall: 0.4906 - tn: 93961.6562 - tp: 81.3516 - val_Brier score: 4.8831e-04 - val_accuracy: 0.9995 - val_auc: 0.9328 - val_cross entropy: 0.0030 - val_fn: 18.0000 - val_fp: 7.0000 - val_loss: 0.0030 - val_prc: 0.8190 - val_precision: 0.9014 - val_recall: 0.7805 - val_tn: 45480.0000 - val_tp: 64.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 0.0013 - accuracy: 0.9985 - auc: 0.4907 - cross entropy: 0.0076 - fn: 1.0000 - fp: 2.0000 - loss: 0.0076 - prc: 4.6001e-04 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2045.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.6257e-04 - accuracy: 0.9989 - auc: 0.8905 - cross entropy: 0.0055 - fn: 24.0769 - fp: 6.5385 - loss: 0.0055 - prc: 0.6043 - precision: 0.7427 - recall: 0.4944 - tn: 27591.5762 - tp: 25.8077 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.7424e-04 - accuracy: 0.9989 - auc: 0.8888 - cross entropy: 0.0057 - fn: 46.5490 - fp: 12.5686 - loss: 0.0057 - prc: 0.5865 - precision: 0.7589 - recall: 0.4889 - tn: 53143.9414 - tp: 44.9412"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.6357e-04 - accuracy: 0.9989 - auc: 0.8885 - cross entropy: 0.0057 - fn: 69.0649 - fp: 17.7792 - loss: 0.0057 - prc: 0.5819 - precision: 0.7716 - recall: 0.4896 - tn: 79718.3672 - tp: 66.7922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 9.5687e-04 - accuracy: 0.9989 - auc: 0.8888 - cross entropy: 0.0057 - fn: 80.5934 - fp: 20.6374 - loss: 0.0057 - prc: 0.5832 - precision: 0.7764 - recall: 0.4924 - tn: 93959.9766 - tp: 79.3626 - val_Brier score: 4.8348e-04 - val_accuracy: 0.9994 - val_auc: 0.9327 - val_cross entropy: 0.0029 - val_fn: 19.0000 - val_fp: 7.0000 - val_loss: 0.0029 - val_prc: 0.8328 - val_precision: 0.9000 - val_recall: 0.7683 - val_tn: 45480.0000 - val_tp: 63.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0015 - accuracy: 0.9980 - auc: 0.7471 - cross entropy: 0.0085 - fn: 4.0000 - fp: 0.0000e+00 - loss: 0.0085 - prc: 0.5026 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2044.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0011 - accuracy: 0.9988 - auc: 0.9101 - cross entropy: 0.0059 - fn: 24.1154 - fp: 8.2692 - loss: 0.0059 - prc: 0.6394 - precision: 0.7617 - recall: 0.5225 - tn: 27585.8086 - tp: 29.8077 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0010 - accuracy: 0.9988 - auc: 0.9146 - cross entropy: 0.0056 - fn: 46.9615 - fp: 14.7885 - loss: 0.0056 - prc: 0.6461 - precision: 0.7745 - recall: 0.5293 - tn: 54155.4219 - tp: 54.8269"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.8136e-04 - accuracy: 0.9989 - auc: 0.9150 - cross entropy: 0.0054 - fn: 68.7403 - fp: 18.0390 - loss: 0.0054 - prc: 0.6518 - precision: 0.7924 - recall: 0.5248 - tn: 79708.8203 - tp: 76.4026"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 9.6310e-04 - accuracy: 0.9989 - auc: 0.9151 - cross entropy: 0.0054 - fn: 79.7912 - fp: 19.9341 - loss: 0.0054 - prc: 0.6522 - precision: 0.7985 - recall: 0.5236 - tn: 93953.0469 - tp: 87.8022 - val_Brier score: 4.6162e-04 - val_accuracy: 0.9995 - val_auc: 0.9449 - val_cross entropy: 0.0028 - val_fn: 16.0000 - val_fp: 8.0000 - val_loss: 0.0028 - val_prc: 0.8431 - val_precision: 0.8919 - val_recall: 0.8049 - val_tn: 45479.0000 - val_tp: 66.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 8/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 0.0022 - accuracy: 0.9976 - auc: 0.7458 - cross entropy: 0.0124 - fn: 4.0000 - fp: 1.0000 - loss: 0.0124 - prc: 0.3157 - precision: 0.6667 - recall: 0.3333 - tn: 2041.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0010 - accuracy: 0.9989 - auc: 0.8471 - cross entropy: 0.0064 - fn: 21.0800 - fp: 6.6000 - loss: 0.0064 - prc: 0.4969 - precision: 0.7735 - recall: 0.5104 - tn: 26573.7207 - tp: 22.6000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.5419e-04 - accuracy: 0.9989 - auc: 0.8696 - cross entropy: 0.0058 - fn: 41.2400 - fp: 12.1200 - loss: 0.0058 - prc: 0.5544 - precision: 0.7828 - recall: 0.5172 - tn: 52125.3789 - tp: 45.2600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m75/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.1106e-04 - accuracy: 0.9990 - auc: 0.8811 - cross entropy: 0.0055 - fn: 60.4000 - fp: 16.2133 - loss: 0.0055 - prc: 0.5902 - precision: 0.7991 - recall: 0.5286 - tn: 77676.7031 - tp: 70.6800"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 8.9193e-04 - accuracy: 0.9990 - auc: 0.8859 - cross entropy: 0.0054 - fn: 72.3516 - fp: 18.9670 - loss: 0.0054 - prc: 0.6052 - precision: 0.8055 - recall: 0.5336 - tn: 93962.6172 - tp: 86.6374 - val_Brier score: 4.4717e-04 - val_accuracy: 0.9995 - val_auc: 0.9509 - val_cross entropy: 0.0027 - val_fn: 16.0000 - val_fp: 8.0000 - val_loss: 0.0027 - val_prc: 0.8545 - val_precision: 0.8919 - val_recall: 0.8049 - val_tn: 45479.0000 - val_tp: 66.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 0.0015 - accuracy: 0.9985 - auc: 0.6617 - cross entropy: 0.0099 - fn: 2.0000 - fp: 1.0000 - loss: 0.0099 - prc: 0.1687 - precision: 0.5000 - recall: 0.3333 - tn: 2044.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0894e-04 - accuracy: 0.9991 - auc: 0.8921 - cross entropy: 0.0049 - fn: 19.9259 - fp: 5.2963 - loss: 0.0049 - prc: 0.5856 - precision: 0.7848 - recall: 0.5640 - tn: 28617.5176 - tp: 29.2593"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m53/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2424e-04 - accuracy: 0.9991 - auc: 0.8953 - cross entropy: 0.0049 - fn: 42.1698 - fp: 10.0377 - loss: 0.0049 - prc: 0.6235 - precision: 0.8162 - recall: 0.5617 - tn: 55188.8125 - tp: 54.9811"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m79/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.3904e-04 - accuracy: 0.9990 - auc: 0.8981 - cross entropy: 0.0050 - fn: 64.4177 - fp: 16.3924 - loss: 0.0050 - prc: 0.6346 - precision: 0.8168 - recall: 0.5565 - tn: 81758.7578 - tp: 80.4304"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 8.3613e-04 - accuracy: 0.9990 - auc: 0.8997 - cross entropy: 0.0049 - fn: 73.0000 - fp: 19.3956 - loss: 0.0049 - prc: 0.6382 - precision: 0.8158 - recall: 0.5571 - tn: 93956.5312 - tp: 91.6484 - val_Brier score: 4.3421e-04 - val_accuracy: 0.9995 - val_auc: 0.9571 - val_cross entropy: 0.0025 - val_fn: 16.0000 - val_fp: 8.0000 - val_loss: 0.0025 - val_prc: 0.8708 - val_precision: 0.8919 - val_recall: 0.8049 - val_tn: 45479.0000 - val_tp: 66.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 10/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 5.0903e-04 - accuracy: 0.9995 - auc: 0.9970 - cross entropy: 0.0034 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0034 - prc: 0.7084 - precision: 1.0000 - recall: 0.6667 - tn: 2045.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.1275e-04 - accuracy: 0.9991 - auc: 0.9393 - cross entropy: 0.0047 - fn: 24.1923 - fp: 3.2692 - loss: 0.0047 - prc: 0.6942 - precision: 0.9098 - recall: 0.5348 - tn: 27594.0762 - tp: 26.4615 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2387e-04 - accuracy: 0.9991 - auc: 0.9353 - cross entropy: 0.0047 - fn: 43.6471 - fp: 7.9216 - loss: 0.0047 - prc: 0.6891 - precision: 0.8874 - recall: 0.5452 - tn: 53143.7070 - tp: 52.7255"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2796e-04 - accuracy: 0.9991 - auc: 0.9310 - cross entropy: 0.0047 - fn: 64.1299 - fp: 12.0390 - loss: 0.0047 - prc: 0.6833 - precision: 0.8793 - recall: 0.5464 - tn: 79717.8828 - tp: 77.9481"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 8.2062e-04 - accuracy: 0.9991 - auc: 0.9295 - cross entropy: 0.0047 - fn: 73.4615 - fp: 14.4176 - loss: 0.0047 - prc: 0.6825 - precision: 0.8762 - recall: 0.5505 - tn: 93960.9688 - tp: 91.7253 - val_Brier score: 4.3984e-04 - val_accuracy: 0.9995 - val_auc: 0.9571 - val_cross entropy: 0.0025 - val_fn: 16.0000 - val_fp: 8.0000 - val_loss: 0.0025 - val_prc: 0.8678 - val_precision: 0.8919 - val_recall: 0.8049 - val_tn: 45479.0000 - val_tp: 66.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 11/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 0.0011 - accuracy: 0.9985 - auc: 0.8740 - cross entropy: 0.0060 - fn: 3.0000 - fp: 0.0000e+00 - loss: 0.0060 - prc: 0.7518 - precision: 1.0000 - recall: 0.2500 - tn: 2044.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.3681e-04 - accuracy: 0.9991 - auc: 0.9300 - cross entropy: 0.0040 - fn: 22.0000 - fp: 4.1481 - loss: 0.0040 - prc: 0.7141 - precision: 0.8671 - recall: 0.5064 - tn: 28624.0742 - tp: 21.7778"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m53/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.7205e-04 - accuracy: 0.9991 - auc: 0.9217 - cross entropy: 0.0042 - fn: 41.9434 - fp: 9.6792 - loss: 0.0042 - prc: 0.6813 - precision: 0.8405 - recall: 0.5102 - tn: 55200.6602 - tp: 43.7170"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m79/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.9157e-04 - accuracy: 0.9991 - auc: 0.9171 - cross entropy: 0.0043 - fn: 62.3165 - fp: 15.7468 - loss: 0.0043 - prc: 0.6668 - precision: 0.8275 - recall: 0.5146 - tn: 81775.0859 - tp: 66.8481"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.9813e-04 - accuracy: 0.9991 - auc: 0.9156 - cross entropy: 0.0044 - fn: 72.3407 - fp: 18.0659 - loss: 0.0044 - prc: 0.6653 - precision: 0.8269 - recall: 0.5163 - tn: 93971.7344 - tp: 78.4286 - val_Brier score: 4.2948e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0025 - val_fn: 16.0000 - val_fp: 8.0000 - val_loss: 0.0025 - val_prc: 0.8749 - val_precision: 0.8919 - val_recall: 0.8049 - val_tn: 45479.0000 - val_tp: 66.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 12/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 0.0012 - accuracy: 0.9985 - auc: 0.8735 - cross entropy: 0.0079 - fn: 2.0000 - fp: 1.0000 - loss: 0.0079 - prc: 0.7533 - precision: 0.8571 - recall: 0.7500 - tn: 2039.0000 - tp: 6.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.1349e-04 - accuracy: 0.9990 - auc: 0.8719 - cross entropy: 0.0050 - fn: 19.0385 - fp: 8.5385 - loss: 0.0050 - prc: 0.6183 - precision: 0.7481 - recall: 0.6015 - tn: 27594.9238 - tp: 25.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2927e-04 - accuracy: 0.9990 - auc: 0.8833 - cross entropy: 0.0049 - fn: 40.7308 - fp: 14.2500 - loss: 0.0049 - prc: 0.6207 - precision: 0.7579 - recall: 0.5613 - tn: 54170.1914 - tp: 46.8269"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0377e-04 - accuracy: 0.9990 - auc: 0.8915 - cross entropy: 0.0047 - fn: 58.5897 - fp: 17.8205 - loss: 0.0047 - prc: 0.6428 - precision: 0.7830 - recall: 0.5638 - tn: 80746.6172 - tp: 72.9744"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.9645e-04 - accuracy: 0.9990 - auc: 0.8946 - cross entropy: 0.0046 - fn: 67.5824 - fp: 19.9231 - loss: 0.0046 - prc: 0.6488 - precision: 0.7907 - recall: 0.5660 - tn: 93966.6719 - tp: 86.3956 - val_Brier score: 4.2749e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0025 - val_fn: 13.0000 - val_fp: 8.0000 - val_loss: 0.0025 - val_prc: 0.8747 - val_precision: 0.8961 - val_recall: 0.8415 - val_tn: 45479.0000 - val_tp: 69.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 13/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 6.9542e-04 - accuracy: 0.9990 - auc: 0.8734 - cross entropy: 0.0051 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0051 - prc: 0.7517 - precision: 1.0000 - recall: 0.5000 - tn: 2044.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.7275e-04 - accuracy: 0.9990 - auc: 0.9131 - cross entropy: 0.0046 - fn: 21.8148 - fp: 6.5556 - loss: 0.0046 - prc: 0.7256 - precision: 0.8622 - recall: 0.5705 - tn: 28613.0742 - tp: 30.5556 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m53/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.9820e-04 - accuracy: 0.9990 - auc: 0.9185 - cross entropy: 0.0047 - fn: 39.3208 - fp: 15.1321 - loss: 0.0047 - prc: 0.7077 - precision: 0.8280 - recall: 0.5930 - tn: 55180.3203 - tp: 61.2264"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0118e-04 - accuracy: 0.9990 - auc: 0.9190 - cross entropy: 0.0047 - fn: 57.5769 - fp: 20.9231 - loss: 0.0047 - prc: 0.6986 - precision: 0.8221 - recall: 0.5941 - tn: 80730.4844 - tp: 87.0128"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.9827e-04 - accuracy: 0.9990 - auc: 0.9186 - cross entropy: 0.0047 - fn: 67.0220 - fp: 22.9341 - loss: 0.0047 - prc: 0.6959 - precision: 0.8234 - recall: 0.5924 - tn: 93951.3984 - tp: 99.2198 - val_Brier score: 4.1913e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0024 - val_fn: 14.0000 - val_fp: 8.0000 - val_loss: 0.0024 - val_prc: 0.8769 - val_precision: 0.8947 - val_recall: 0.8293 - val_tn: 45479.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 14/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 4.9113e-04 - accuracy: 0.9995 - auc: 0.7473 - cross entropy: 0.0054 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0054 - prc: 0.5013 - precision: 1.0000 - recall: 0.5000 - tn: 2046.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7095e-04 - accuracy: 0.9993 - auc: 0.8609 - cross entropy: 0.0047 - fn: 17.0000 - fp: 2.2500 - loss: 0.0047 - prc: 0.6641 - precision: 0.9330 - recall: 0.5806 - tn: 25556.0840 - tp: 24.6667 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7074e-04 - accuracy: 0.9993 - auc: 0.8847 - cross entropy: 0.0044 - fn: 31.1915 - fp: 6.4468 - loss: 0.0044 - prc: 0.6905 - precision: 0.9091 - recall: 0.6065 - tn: 49063.1484 - tp: 51.2128"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m70/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8407e-04 - accuracy: 0.9992 - auc: 0.8949 - cross entropy: 0.0043 - fn: 46.0857 - fp: 11.9571 - loss: 0.0043 - prc: 0.7014 - precision: 0.8898 - recall: 0.6152 - tn: 72568.1562 - tp: 77.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.9193e-04 - accuracy: 0.9992 - auc: 0.8996 - cross entropy: 0.0043 - fn: 60.7692 - fp: 15.8462 - loss: 0.0043 - prc: 0.7059 - precision: 0.8820 - recall: 0.6140 - tn: 93964.6172 - tp: 99.3407 - val_Brier score: 4.0537e-04 - val_accuracy: 0.9995 - val_auc: 0.9571 - val_cross entropy: 0.0024 - val_fn: 14.0000 - val_fp: 8.0000 - val_loss: 0.0024 - val_prc: 0.8751 - val_precision: 0.8947 - val_recall: 0.8293 - val_tn: 45479.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 15/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0022 - accuracy: 0.9971 - auc: 0.8547 - cross entropy: 0.0113 - fn: 6.0000 - fp: 0.0000e+00 - loss: 0.0113 - prc: 0.5775 - precision: 1.0000 - recall: 0.1429 - tn: 2041.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m23/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0010 - accuracy: 0.9987 - auc: 0.8995 - cross entropy: 0.0055 - fn: 23.0435 - fp: 4.6087 - loss: 0.0055 - prc: 0.5795 - precision: 0.7756 - recall: 0.3747 - tn: 24532.2617 - tp: 16.0870 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.2955e-04 - accuracy: 0.9989 - auc: 0.9036 - cross entropy: 0.0050 - fn: 41.0638 - fp: 8.9787 - loss: 0.0050 - prc: 0.6205 - precision: 0.8005 - recall: 0.4496 - tn: 49061.5547 - tp: 40.4043"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m71/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.9463e-04 - accuracy: 0.9989 - auc: 0.9062 - cross entropy: 0.0049 - fn: 59.4225 - fp: 13.2254 - loss: 0.0049 - prc: 0.6351 - precision: 0.8124 - recall: 0.4782 - tn: 73591.5625 - tp: 63.7887"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 8.7191e-04 - accuracy: 0.9990 - auc: 0.9083 - cross entropy: 0.0048 - fn: 73.3297 - fp: 16.7253 - loss: 0.0048 - prc: 0.6461 - precision: 0.8193 - recall: 0.4967 - tn: 93966.0078 - tp: 84.5055 - val_Brier score: 4.0166e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0023 - val_fn: 14.0000 - val_fp: 8.0000 - val_loss: 0.0023 - val_prc: 0.8796 - val_precision: 0.8947 - val_recall: 0.8293 - val_tn: 45479.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 16/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 4.3094e-05 - accuracy: 1.0000 - auc: 1.0000 - cross entropy: 7.2283e-04 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 7.2283e-04 - prc: 1.0000 - precision: 1.0000 - recall: 1.0000 - tn: 2047.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5800e-04 - accuracy: 0.9991 - auc: 0.9234 - cross entropy: 0.0042 - fn: 20.6667 - fp: 6.2963 - loss: 0.0042 - prc: 0.7231 - precision: 0.8370 - recall: 0.6196 - tn: 28613.8145 - tp: 31.2222 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m53/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.8812e-04 - accuracy: 0.9991 - auc: 0.9268 - cross entropy: 0.0043 - fn: 40.6226 - fp: 12.2075 - loss: 0.0043 - prc: 0.7071 - precision: 0.8295 - recall: 0.6000 - tn: 55185.6992 - tp: 57.4717"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m79/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.7441e-04 - accuracy: 0.9991 - auc: 0.9271 - cross entropy: 0.0042 - fn: 57.2785 - fp: 16.4051 - loss: 0.0042 - prc: 0.7072 - precision: 0.8362 - recall: 0.6025 - tn: 81761.1016 - tp: 85.2152"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.7092e-04 - accuracy: 0.9991 - auc: 0.9261 - cross entropy: 0.0042 - fn: 65.2308 - fp: 18.3187 - loss: 0.0042 - prc: 0.7057 - precision: 0.8384 - recall: 0.6026 - tn: 93959.4844 - tp: 97.5385 - val_Brier score: 3.9099e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0023 - val_fn: 14.0000 - val_fp: 8.0000 - val_loss: 0.0023 - val_prc: 0.8793 - val_precision: 0.8947 - val_recall: 0.8293 - val_tn: 45479.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 17/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 4.1629e-04 - accuracy: 0.9995 - auc: 0.9998 - cross entropy: 0.0018 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0018 - prc: 0.7973 - precision: 1.0000 - recall: 0.5000 - tn: 2046.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.4939e-04 - accuracy: 0.9994 - auc: 0.9742 - cross entropy: 0.0029 - fn: 13.0370 - fp: 6.4074 - loss: 0.0029 - prc: 0.7614 - precision: 0.8455 - recall: 0.7289 - tn: 28622.5547 - tp: 30.0000 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m53/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.0406e-04 - accuracy: 0.9993 - auc: 0.9618 - cross entropy: 0.0032 - fn: 29.6226 - fp: 10.8113 - loss: 0.0032 - prc: 0.7395 - precision: 0.8452 - recall: 0.6856 - tn: 55199.4141 - tp: 56.1509"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m80/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.6247e-04 - accuracy: 0.9993 - auc: 0.9522 - cross entropy: 0.0035 - fn: 51.2875 - fp: 16.9625 - loss: 0.0035 - prc: 0.7250 - precision: 0.8393 - recall: 0.6561 - tn: 82791.5234 - tp: 84.2250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.7751e-04 - accuracy: 0.9992 - auc: 0.9493 - cross entropy: 0.0036 - fn: 60.1648 - fp: 19.0440 - loss: 0.0036 - prc: 0.7219 - precision: 0.8393 - recall: 0.6479 - tn: 93965.7891 - tp: 95.5714 - val_Brier score: 3.9969e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0023 - val_fn: 13.0000 - val_fp: 8.0000 - val_loss: 0.0023 - val_prc: 0.8798 - val_precision: 0.8961 - val_recall: 0.8415 - val_tn: 45479.0000 - val_tp: 69.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 18/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 5.5516e-04 - accuracy: 0.9995 - auc: 0.9998 - cross entropy: 0.0030 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0030 - prc: 0.9288 - precision: 1.0000 - recall: 0.8000 - tn: 2043.0000 - tp: 4.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.0313e-04 - accuracy: 0.9993 - auc: 0.9406 - cross entropy: 0.0035 - fn: 12.8077 - fp: 6.8077 - loss: 0.0035 - prc: 0.7754 - precision: 0.8547 - recall: 0.7241 - tn: 27596.1914 - tp: 32.1923 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3922e-04 - accuracy: 0.9992 - auc: 0.9321 - cross entropy: 0.0036 - fn: 29.3529 - fp: 13.0588 - loss: 0.0036 - prc: 0.7538 - precision: 0.8316 - recall: 0.6837 - tn: 53148.6094 - tp: 56.9804"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5616e-04 - accuracy: 0.9992 - auc: 0.9292 - cross entropy: 0.0037 - fn: 45.5789 - fp: 18.1711 - loss: 0.0037 - prc: 0.7439 - precision: 0.8303 - recall: 0.6684 - tn: 78700.8281 - tp: 83.4211"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.7281e-04 - accuracy: 0.9992 - auc: 0.9265 - cross entropy: 0.0038 - fn: 56.6483 - fp: 21.4066 - loss: 0.0038 - prc: 0.7349 - precision: 0.8293 - recall: 0.6590 - tn: 93963.6016 - tp: 98.9121 - val_Brier score: 3.8850e-04 - val_accuracy: 0.9995 - val_auc: 0.9631 - val_cross entropy: 0.0023 - val_fn: 14.0000 - val_fp: 8.0000 - val_loss: 0.0023 - val_prc: 0.8806 - val_precision: 0.8947 - val_recall: 0.8293 - val_tn: 45479.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 19/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 7.3613e-04 - accuracy: 0.9990 - auc: 0.9998 - cross entropy: 0.0031 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0031 - prc: 0.9288 - precision: 1.0000 - recall: 0.6000 - tn: 2043.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.0281e-04 - accuracy: 0.9990 - auc: 0.9217 - cross entropy: 0.0049 - fn: 25.8148 - fp: 3.9259 - loss: 0.0049 - prc: 0.7434 - precision: 0.9221 - recall: 0.5377 - tn: 28611.3711 - tp: 30.8889 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m53/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.7033e-04 - accuracy: 0.9990 - auc: 0.9170 - cross entropy: 0.0047 - fn: 45.6038 - fp: 8.5849 - loss: 0.0047 - prc: 0.7279 - precision: 0.8957 - recall: 0.5537 - tn: 55182.9805 - tp: 58.8302"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m79/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.3161e-04 - accuracy: 0.9990 - auc: 0.9160 - cross entropy: 0.0046 - fn: 60.4304 - fp: 13.9494 - loss: 0.0046 - prc: 0.7132 - precision: 0.8782 - recall: 0.5671 - tn: 81762.5312 - tp: 83.0886"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 8.2819e-04 - accuracy: 0.9991 - auc: 0.9152 - cross entropy: 0.0045 - fn: 68.9670 - fp: 16.4615 - loss: 0.0045 - prc: 0.7070 - precision: 0.8723 - recall: 0.5674 - tn: 93961.1875 - tp: 93.9560 - val_Brier score: 3.7945e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0022 - val_fn: 15.0000 - val_fp: 4.0000 - val_loss: 0.0022 - val_prc: 0.8846 - val_precision: 0.9437 - val_recall: 0.8171 - val_tn: 45483.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 20/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 8.5844e-04 - accuracy: 0.9990 - auc: 0.9997 - cross entropy: 0.0030 - fn: 1.0000 - fp: 1.0000 - loss: 0.0030 - prc: 0.7690 - precision: 0.6667 - recall: 0.6667 - tn: 2044.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5351e-04 - accuracy: 0.9992 - auc: 0.9276 - cross entropy: 0.0034 - fn: 17.3600 - fp: 4.3600 - loss: 0.0034 - prc: 0.7667 - precision: 0.8326 - recall: 0.6345 - tn: 26576.9199 - tp: 25.3600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8994e-04 - accuracy: 0.9992 - auc: 0.9222 - cross entropy: 0.0037 - fn: 35.8980 - fp: 7.2041 - loss: 0.0037 - prc: 0.7536 - precision: 0.8586 - recall: 0.6106 - tn: 51105.5938 - tp: 51.3061"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.1891e-04 - accuracy: 0.9992 - auc: 0.9190 - cross entropy: 0.0039 - fn: 55.2055 - fp: 11.7808 - loss: 0.0039 - prc: 0.7404 - precision: 0.8581 - recall: 0.5984 - tn: 75632.9297 - tp: 76.0822"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.3339e-04 - accuracy: 0.9991 - auc: 0.9177 - cross entropy: 0.0040 - fn: 69.4066 - fp: 15.1868 - loss: 0.0040 - prc: 0.7302 - precision: 0.8563 - recall: 0.5912 - tn: 93962.6797 - tp: 93.2967 - val_Brier score: 3.9398e-04 - val_accuracy: 0.9996 - val_auc: 0.9631 - val_cross entropy: 0.0023 - val_fn: 12.0000 - val_fp: 8.0000 - val_loss: 0.0023 - val_prc: 0.8820 - val_precision: 0.8974 - val_recall: 0.8537 - val_tn: 45479.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 21/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 9.8651e-04 - accuracy: 0.9990 - auc: 0.9153 - cross entropy: 0.0066 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0066 - prc: 0.7250 - precision: 1.0000 - recall: 0.6667 - tn: 2042.0000 - tp: 4.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.6814e-04 - accuracy: 0.9993 - auc: 0.9422 - cross entropy: 0.0033 - fn: 15.3077 - fp: 4.5385 - loss: 0.0033 - prc: 0.7955 - precision: 0.8974 - recall: 0.6636 - tn: 27598.0391 - tp: 30.1154 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.0300e-04 - accuracy: 0.9993 - auc: 0.9348 - cross entropy: 0.0035 - fn: 29.5098 - fp: 9.6275 - loss: 0.0035 - prc: 0.7655 - precision: 0.8770 - recall: 0.6659 - tn: 53150.1758 - tp: 58.6863"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3111e-04 - accuracy: 0.9993 - auc: 0.9294 - cross entropy: 0.0037 - fn: 47.8312 - fp: 14.1429 - loss: 0.0037 - prc: 0.7497 - precision: 0.8695 - recall: 0.6500 - tn: 79725.6484 - tp: 84.3766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.4973e-04 - accuracy: 0.9992 - auc: 0.9275 - cross entropy: 0.0037 - fn: 58.8681 - fp: 16.9231 - loss: 0.0037 - prc: 0.7428 - precision: 0.8653 - recall: 0.6408 - tn: 93966.9141 - tp: 97.8681 - val_Brier score: 3.7917e-04 - val_accuracy: 0.9996 - val_auc: 0.9631 - val_cross entropy: 0.0022 - val_fn: 13.0000 - val_fp: 6.0000 - val_loss: 0.0022 - val_prc: 0.8842 - val_precision: 0.9200 - val_recall: 0.8415 - val_tn: 45481.0000 - val_tp: 69.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 22/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 1.0280e-04 - accuracy: 1.0000 - auc: 1.0000 - cross entropy: 7.2116e-04 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 7.2116e-04 - prc: 1.0000 - precision: 1.0000 - recall: 1.0000 - tn: 2046.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.3697e-04 - accuracy: 0.9990 - auc: 0.9318 - cross entropy: 0.0045 - fn: 22.7600 - fp: 4.1200 - loss: 0.0045 - prc: 0.7145 - precision: 0.8437 - recall: 0.5491 - tn: 26570.1992 - tp: 26.9200 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.1623e-04 - accuracy: 0.9990 - auc: 0.9244 - cross entropy: 0.0045 - fn: 38.7755 - fp: 9.1633 - loss: 0.0045 - prc: 0.7064 - precision: 0.8480 - recall: 0.5756 - tn: 51096.5117 - tp: 55.5510"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m74/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.9044e-04 - accuracy: 0.9991 - auc: 0.9220 - cross entropy: 0.0044 - fn: 54.4054 - fp: 13.9459 - loss: 0.0044 - prc: 0.7041 - precision: 0.8501 - recall: 0.5886 - tn: 76649.2031 - tp: 82.4459"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.8078e-04 - accuracy: 0.9991 - auc: 0.9217 - cross entropy: 0.0043 - fn: 65.3407 - fp: 17.4835 - loss: 0.0043 - prc: 0.7030 - precision: 0.8490 - recall: 0.5930 - tn: 93957.4062 - tp: 100.3407 - val_Brier score: 3.6988e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0022 - val_fn: 15.0000 - val_fp: 4.0000 - val_loss: 0.0022 - val_prc: 0.8860 - val_precision: 0.9437 - val_recall: 0.8171 - val_tn: 45483.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 23/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 7.1992e-04 - accuracy: 0.9990 - auc: 0.9995 - cross entropy: 0.0028 - fn: 0.0000e+00 - fp: 2.0000 - loss: 0.0028 - prc: 0.7123 - precision: 0.5000 - recall: 1.0000 - tn: 2044.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.9079e-04 - accuracy: 0.9993 - auc: 0.9364 - cross entropy: 0.0032 - fn: 12.4615 - fp: 4.5769 - loss: 0.0032 - prc: 0.7198 - precision: 0.8263 - recall: 0.7107 - tn: 27601.5000 - tp: 29.4615 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.0390e-04 - accuracy: 0.9993 - auc: 0.9312 - cross entropy: 0.0034 - fn: 30.2115 - fp: 8.7115 - loss: 0.0034 - prc: 0.7294 - precision: 0.8449 - recall: 0.6716 - tn: 54178.3672 - tp: 54.7115"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4547e-04 - accuracy: 0.9993 - auc: 0.9291 - cross entropy: 0.0036 - fn: 50.2308 - fp: 14.0769 - loss: 0.0036 - prc: 0.7247 - precision: 0.8462 - recall: 0.6499 - tn: 80748.8828 - tp: 82.8077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.5680e-04 - accuracy: 0.9992 - auc: 0.9284 - cross entropy: 0.0037 - fn: 59.4396 - fp: 16.5934 - loss: 0.0037 - prc: 0.7232 - precision: 0.8467 - recall: 0.6442 - tn: 93967.9141 - tp: 96.6264 - val_Brier score: 3.8501e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0022 - val_fn: 12.0000 - val_fp: 8.0000 - val_loss: 0.0022 - val_prc: 0.8874 - val_precision: 0.8974 - val_recall: 0.8537 - val_tn: 45479.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 24/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 0.0014 - accuracy: 0.9980 - auc: 0.9996 - cross entropy: 0.0051 - fn: 1.0000 - fp: 3.0000 - loss: 0.0051 - prc: 0.8844 - precision: 0.5000 - recall: 0.7500 - tn: 2041.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2411e-04 - accuracy: 0.9990 - auc: 0.9577 - cross entropy: 0.0042 - fn: 18.7200 - fp: 8.2000 - loss: 0.0042 - prc: 0.7223 - precision: 0.7394 - recall: 0.6537 - tn: 26566.8398 - tp: 30.2400"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0100e-04 - accuracy: 0.9990 - auc: 0.9433 - cross entropy: 0.0043 - fn: 36.1600 - fp: 12.3400 - loss: 0.0043 - prc: 0.7147 - precision: 0.7877 - recall: 0.6320 - tn: 52118.0000 - tp: 57.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.7020e-04 - accuracy: 0.9991 - auc: 0.9374 - cross entropy: 0.0042 - fn: 52.6316 - fp: 16.0789 - loss: 0.0042 - prc: 0.7156 - precision: 0.8111 - recall: 0.6287 - tn: 78693.9844 - tp: 85.3026"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.6319e-04 - accuracy: 0.9991 - auc: 0.9350 - cross entropy: 0.0042 - fn: 62.4835 - fp: 18.8681 - loss: 0.0042 - prc: 0.7144 - precision: 0.8168 - recall: 0.6266 - tn: 93958.2656 - tp: 100.9560 - val_Brier score: 3.7177e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0022 - val_fn: 13.0000 - val_fp: 4.0000 - val_loss: 0.0022 - val_prc: 0.8853 - val_precision: 0.9452 - val_recall: 0.8415 - val_tn: 45483.0000 - val_tp: 69.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 25/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0014 - accuracy: 0.9980 - auc: 0.9995 - cross entropy: 0.0042 - fn: 3.0000 - fp: 1.0000 - loss: 0.0042 - prc: 0.8433 - precision: 0.7500 - recall: 0.5000 - tn: 2041.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.8691e-04 - accuracy: 0.9989 - auc: 0.9424 - cross entropy: 0.0041 - fn: 19.6400 - fp: 6.9600 - loss: 0.0041 - prc: 0.7102 - precision: 0.7852 - recall: 0.5518 - tn: 26571.0391 - tp: 26.3600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.1432e-04 - accuracy: 0.9990 - auc: 0.9377 - cross entropy: 0.0041 - fn: 36.5306 - fp: 10.1633 - loss: 0.0041 - prc: 0.7090 - precision: 0.8185 - recall: 0.5736 - tn: 51100.8359 - tp: 52.4694"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m74/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.8811e-04 - accuracy: 0.9990 - auc: 0.9338 - cross entropy: 0.0041 - fn: 53.9730 - fp: 13.8108 - loss: 0.0041 - prc: 0.7068 - precision: 0.8338 - recall: 0.5824 - tn: 76652.7422 - tp: 79.4730"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.7663e-04 - accuracy: 0.9991 - auc: 0.9317 - cross entropy: 0.0041 - fn: 64.8681 - fp: 16.8901 - loss: 0.0041 - prc: 0.7062 - precision: 0.8374 - recall: 0.5877 - tn: 93961.2734 - tp: 97.5385 - val_Brier score: 3.6719e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0022 - val_fn: 16.0000 - val_fp: 4.0000 - val_loss: 0.0022 - val_prc: 0.8856 - val_precision: 0.9429 - val_recall: 0.8049 - val_tn: 45483.0000 - val_tp: 66.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 26/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 3.8111e-04 - accuracy: 0.9995 - auc: 1.0000 - cross entropy: 0.0015 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0015 - prc: 1.0000 - precision: 1.0000 - recall: 0.5000 - tn: 2046.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.4853e-04 - accuracy: 0.9991 - auc: 0.9308 - cross entropy: 0.0041 - fn: 18.4400 - fp: 4.3600 - loss: 0.0041 - prc: 0.7885 - precision: 0.8805 - recall: 0.6184 - tn: 26569.3594 - tp: 31.8400 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5230e-04 - accuracy: 0.9991 - auc: 0.9281 - cross entropy: 0.0041 - fn: 36.0204 - fp: 9.1224 - loss: 0.0041 - prc: 0.7715 - precision: 0.8698 - recall: 0.6144 - tn: 51096.9609 - tp: 57.8980"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.6660e-04 - accuracy: 0.9991 - auc: 0.9260 - cross entropy: 0.0041 - fn: 55.7123 - fp: 13.4795 - loss: 0.0041 - prc: 0.7580 - precision: 0.8661 - recall: 0.6052 - tn: 75623.3984 - tp: 83.4110"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.6326e-04 - accuracy: 0.9991 - auc: 0.9250 - cross entropy: 0.0041 - fn: 68.6813 - fp: 16.3297 - loss: 0.0041 - prc: 0.7517 - precision: 0.8644 - recall: 0.6002 - tn: 93955.5312 - tp: 100.0330 - val_Brier score: 3.8389e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0022 - val_fn: 12.0000 - val_fp: 8.0000 - val_loss: 0.0022 - val_prc: 0.8845 - val_precision: 0.8974 - val_recall: 0.8537 - val_tn: 45479.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 27/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0017 - accuracy: 0.9980 - auc: 0.7449 - cross entropy: 0.0101 - fn: 3.0000 - fp: 1.0000 - loss: 0.0101 - prc: 0.2741 - precision: 0.5000 - recall: 0.2500 - tn: 2043.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.6202e-04 - accuracy: 0.9989 - auc: 0.9047 - cross entropy: 0.0052 - fn: 20.2308 - fp: 7.0385 - loss: 0.0052 - prc: 0.5747 - precision: 0.7237 - recall: 0.5133 - tn: 27592.4609 - tp: 28.2692"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.3925e-04 - accuracy: 0.9990 - auc: 0.9238 - cross entropy: 0.0045 - fn: 34.7059 - fp: 12.2157 - loss: 0.0045 - prc: 0.6556 - precision: 0.7805 - recall: 0.5802 - tn: 53141.7656 - tp: 59.3137"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m75/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0137e-04 - accuracy: 0.9991 - auc: 0.9274 - cross entropy: 0.0043 - fn: 50.9200 - fp: 16.2533 - loss: 0.0043 - prc: 0.6770 - precision: 0.8017 - recall: 0.5920 - tn: 77672.5312 - tp: 84.2933"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.8576e-04 - accuracy: 0.9991 - auc: 0.9288 - cross entropy: 0.0042 - fn: 61.5165 - fp: 18.7802 - loss: 0.0042 - prc: 0.6859 - precision: 0.8108 - recall: 0.5962 - tn: 93959.4844 - tp: 100.7912 - val_Brier score: 3.6900e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 6.0000 - val_loss: 0.0021 - val_prc: 0.8899 - val_precision: 0.9211 - val_recall: 0.8537 - val_tn: 45481.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 28/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 0.0013 - accuracy: 0.9985 - auc: 0.9998 - cross entropy: 0.0047 - fn: 2.0000 - fp: 1.0000 - loss: 0.0047 - prc: 0.8723 - precision: 0.6667 - recall: 0.5000 - tn: 2043.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.2289e-04 - accuracy: 0.9989 - auc: 0.9120 - cross entropy: 0.0047 - fn: 21.3077 - fp: 8.2692 - loss: 0.0047 - prc: 0.5834 - precision: 0.6899 - recall: 0.5179 - tn: 27596.8086 - tp: 21.6154"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.9797e-04 - accuracy: 0.9990 - auc: 0.9156 - cross entropy: 0.0046 - fn: 40.2941 - fp: 12.6078 - loss: 0.0046 - prc: 0.6146 - precision: 0.7502 - recall: 0.5366 - tn: 53146.8828 - tp: 48.2157"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.5397e-04 - accuracy: 0.9990 - auc: 0.9193 - cross entropy: 0.0045 - fn: 56.1053 - fp: 16.7632 - loss: 0.0045 - prc: 0.6379 - precision: 0.7802 - recall: 0.5584 - tn: 78698.5938 - tp: 76.5395"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 8.3276e-04 - accuracy: 0.9991 - auc: 0.9218 - cross entropy: 0.0044 - fn: 65.2527 - fp: 19.2308 - loss: 0.0044 - prc: 0.6487 - precision: 0.7912 - recall: 0.5671 - tn: 93963.1953 - tp: 92.8901 - val_Brier score: 3.6730e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0022 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0022 - val_prc: 0.8855 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 29/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 3.7853e-04 - accuracy: 0.9990 - auc: 1.0000 - cross entropy: 0.0014 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0014 - prc: 1.0000 - precision: 1.0000 - recall: 0.6000 - tn: 2043.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.9173e-04 - accuracy: 0.9993 - auc: 0.9255 - cross entropy: 0.0032 - fn: 19.2593 - fp: 1.5185 - loss: 0.0032 - prc: 0.8126 - precision: 0.9643 - recall: 0.6294 - tn: 28620.3711 - tp: 30.8519 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3518e-04 - accuracy: 0.9992 - auc: 0.9248 - cross entropy: 0.0034 - fn: 36.0769 - fp: 5.8462 - loss: 0.0034 - prc: 0.7836 - precision: 0.9289 - recall: 0.6183 - tn: 54173.6172 - tp: 56.4615"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5944e-04 - accuracy: 0.9992 - auc: 0.9250 - cross entropy: 0.0035 - fn: 52.8831 - fp: 11.6104 - loss: 0.0035 - prc: 0.7673 - precision: 0.9052 - recall: 0.6173 - tn: 79723.6719 - tp: 83.8312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.6513e-04 - accuracy: 0.9992 - auc: 0.9247 - cross entropy: 0.0036 - fn: 61.8352 - fp: 14.6923 - loss: 0.0036 - prc: 0.7626 - precision: 0.8972 - recall: 0.6181 - tn: 93964.9375 - tp: 99.1099 - val_Brier score: 3.6506e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8872 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 30/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 6.6586e-04 - accuracy: 0.9990 - auc: 0.9999 - cross entropy: 0.0024 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0024 - prc: 0.9663 - precision: 1.0000 - recall: 0.7143 - tn: 2041.0000 - tp: 5.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.6405e-04 - accuracy: 0.9990 - auc: 0.9622 - cross entropy: 0.0036 - fn: 19.1154 - fp: 5.6538 - loss: 0.0036 - prc: 0.8059 - precision: 0.8421 - recall: 0.6236 - tn: 27591.6543 - tp: 31.5769 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.0694e-04 - accuracy: 0.9991 - auc: 0.9554 - cross entropy: 0.0035 - fn: 32.8431 - fp: 9.7843 - loss: 0.0035 - prc: 0.7903 - precision: 0.8519 - recall: 0.6369 - tn: 53146.1367 - tp: 59.2353"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.0833e-04 - accuracy: 0.9991 - auc: 0.9478 - cross entropy: 0.0036 - fn: 50.4805 - fp: 14.1688 - loss: 0.0036 - prc: 0.7718 - precision: 0.8551 - recall: 0.6328 - tn: 79720.4141 - tp: 86.9351"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.1007e-04 - accuracy: 0.9991 - auc: 0.9455 - cross entropy: 0.0036 - fn: 60.5385 - fp: 16.3956 - loss: 0.0036 - prc: 0.7654 - precision: 0.8556 - recall: 0.6277 - tn: 93963.3984 - tp: 100.2418 - val_Brier score: 3.6817e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 6.0000 - val_loss: 0.0021 - val_prc: 0.8868 - val_precision: 0.9211 - val_recall: 0.8537 - val_tn: 45481.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 31/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 4.8676e-04 - accuracy: 0.9995 - auc: 0.4976 - cross entropy: 0.0033 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0033 - prc: 4.7786e-04 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2047.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.1796e-04 - accuracy: 0.9993 - auc: 0.8894 - cross entropy: 0.0039 - fn: 17.8462 - fp: 4.5000 - loss: 0.0039 - prc: 0.7097 - precision: 0.8346 - recall: 0.6087 - tn: 27599.0391 - tp: 26.6154 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8226e-04 - accuracy: 0.9992 - auc: 0.9013 - cross entropy: 0.0040 - fn: 36.4902 - fp: 11.2549 - loss: 0.0040 - prc: 0.7022 - precision: 0.8142 - recall: 0.5828 - tn: 53152.1562 - tp: 48.0980"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.9630e-04 - accuracy: 0.9991 - auc: 0.9103 - cross entropy: 0.0039 - fn: 54.4026 - fp: 16.8571 - loss: 0.0039 - prc: 0.7079 - precision: 0.8151 - recall: 0.5820 - tn: 79726.8281 - tp: 73.9091"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.0085e-04 - accuracy: 0.9991 - auc: 0.9130 - cross entropy: 0.0039 - fn: 63.7363 - fp: 20.1429 - loss: 0.0039 - prc: 0.7108 - precision: 0.8159 - recall: 0.5851 - tn: 93967.3516 - tp: 89.3407 - val_Brier score: 3.6721e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 6.0000 - val_loss: 0.0021 - val_prc: 0.8871 - val_precision: 0.9211 - val_recall: 0.8537 - val_tn: 45481.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 32/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 5.1009e-06 - accuracy: 1.0000 - auc: 1.0000 - cross entropy: 4.1149e-04 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 4.1149e-04 - prc: 1.0000 - precision: 1.0000 - recall: 1.0000 - tn: 2047.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.8982e-04 - accuracy: 0.9994 - auc: 0.9323 - cross entropy: 0.0036 - fn: 15.1538 - fp: 5.0385 - loss: 0.0036 - prc: 0.7047 - precision: 0.8756 - recall: 0.7163 - tn: 27597.4609 - tp: 30.3462 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8864e-04 - accuracy: 0.9992 - auc: 0.9266 - cross entropy: 0.0041 - fn: 35.1373 - fp: 10.1176 - loss: 0.0041 - prc: 0.6909 - precision: 0.8613 - recall: 0.6625 - tn: 53145.2539 - tp: 57.4902"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.2641e-04 - accuracy: 0.9992 - auc: 0.9263 - cross entropy: 0.0042 - fn: 55.6364 - fp: 14.4805 - loss: 0.0042 - prc: 0.6909 - precision: 0.8599 - recall: 0.6379 - tn: 79717.2188 - tp: 84.6623"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.2889e-04 - accuracy: 0.9992 - auc: 0.9260 - cross entropy: 0.0042 - fn: 64.7473 - fp: 17.0000 - loss: 0.0042 - prc: 0.6922 - precision: 0.8590 - recall: 0.6338 - tn: 93959.4297 - tp: 99.3956 - val_Brier score: 3.6700e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0022 - val_fn: 12.0000 - val_fp: 6.0000 - val_loss: 0.0022 - val_prc: 0.8861 - val_precision: 0.9211 - val_recall: 0.8537 - val_tn: 45481.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 33/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0013 - accuracy: 0.9985 - auc: 0.8321 - cross entropy: 0.0102 - fn: 3.0000 - fp: 0.0000e+00 - loss: 0.0102 - prc: 0.6701 - precision: 1.0000 - recall: 0.5000 - tn: 2042.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.8331e-04 - accuracy: 0.9990 - auc: 0.8960 - cross entropy: 0.0054 - fn: 20.6000 - fp: 5.5200 - loss: 0.0054 - prc: 0.7034 - precision: 0.8690 - recall: 0.6050 - tn: 26567.4004 - tp: 30.4800"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.0933e-04 - accuracy: 0.9991 - auc: 0.9089 - cross entropy: 0.0047 - fn: 34.5306 - fp: 10.9796 - loss: 0.0047 - prc: 0.7039 - precision: 0.8455 - recall: 0.6066 - tn: 51101.4883 - tp: 53.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m74/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.7977e-04 - accuracy: 0.9991 - auc: 0.9132 - cross entropy: 0.0044 - fn: 51.2432 - fp: 15.9459 - loss: 0.0044 - prc: 0.7075 - precision: 0.8397 - recall: 0.6030 - tn: 76655.9844 - tp: 76.8243"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.6838e-04 - accuracy: 0.9991 - auc: 0.9147 - cross entropy: 0.0043 - fn: 62.1758 - fp: 19.4615 - loss: 0.0043 - prc: 0.7076 - precision: 0.8379 - recall: 0.6039 - tn: 93964.6172 - tp: 94.3187 - val_Brier score: 3.5868e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 15.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8888 - val_precision: 0.9437 - val_recall: 0.8171 - val_tn: 45483.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 34/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 0.0013 - accuracy: 0.9985 - auc: 0.8562 - cross entropy: 0.0076 - fn: 3.0000 - fp: 0.0000e+00 - loss: 0.0076 - prc: 0.7179 - precision: 1.0000 - recall: 0.5714 - tn: 2041.0000 - tp: 4.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.7075e-04 - accuracy: 0.9990 - auc: 0.9231 - cross entropy: 0.0044 - fn: 22.3077 - fp: 4.7692 - loss: 0.0044 - prc: 0.7235 - precision: 0.8969 - recall: 0.5342 - tn: 27593.2305 - tp: 27.6923"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.7073e-04 - accuracy: 0.9991 - auc: 0.9337 - cross entropy: 0.0040 - fn: 34.8235 - fp: 9.9412 - loss: 0.0040 - prc: 0.7435 - precision: 0.8757 - recall: 0.5930 - tn: 53144.2734 - tp: 58.9608"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.2723e-04 - accuracy: 0.9991 - auc: 0.9346 - cross entropy: 0.0038 - fn: 48.4156 - fp: 14.6494 - loss: 0.0038 - prc: 0.7459 - precision: 0.8700 - recall: 0.6158 - tn: 79720.6875 - tp: 88.2467"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.1733e-04 - accuracy: 0.9992 - auc: 0.9340 - cross entropy: 0.0038 - fn: 56.5934 - fp: 16.9560 - loss: 0.0038 - prc: 0.7449 - precision: 0.8692 - recall: 0.6213 - tn: 93963.1562 - tp: 103.8681 - val_Brier score: 3.5923e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 15.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8886 - val_precision: 0.9437 - val_recall: 0.8171 - val_tn: 45483.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 35/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 9.7795e-04 - accuracy: 0.9985 - auc: 0.9995 - cross entropy: 0.0032 - fn: 2.0000 - fp: 1.0000 - loss: 0.0032 - prc: 0.7356 - precision: 0.6667 - recall: 0.5000 - tn: 2043.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.2271e-04 - accuracy: 0.9988 - auc: 0.9431 - cross entropy: 0.0045 - fn: 22.5000 - fp: 6.9615 - loss: 0.0045 - prc: 0.7215 - precision: 0.8137 - recall: 0.5543 - tn: 27586.1914 - tp: 32.3462"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.2577e-04 - accuracy: 0.9990 - auc: 0.9463 - cross entropy: 0.0041 - fn: 37.3469 - fp: 10.0000 - loss: 0.0041 - prc: 0.7345 - precision: 0.8349 - recall: 0.5769 - tn: 51096.9805 - tp: 55.6735"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.8784e-04 - accuracy: 0.9990 - auc: 0.9418 - cross entropy: 0.0040 - fn: 53.1644 - fp: 13.8082 - loss: 0.0040 - prc: 0.7316 - precision: 0.8408 - recall: 0.5829 - tn: 75630.5078 - tp: 78.5205"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 7.7370e-04 - accuracy: 0.9991 - auc: 0.9391 - cross entropy: 0.0040 - fn: 65.4835 - fp: 16.2308 - loss: 0.0040 - prc: 0.7310 - precision: 0.8463 - recall: 0.5861 - tn: 93961.7578 - tp: 97.0989 - val_Brier score: 3.6408e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8937 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 36/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 6.0666e-04 - accuracy: 0.9990 - auc: 1.0000 - cross entropy: 0.0020 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0020 - prc: 1.0000 - precision: 1.0000 - recall: 0.3333 - tn: 2045.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4407e-04 - accuracy: 0.9993 - auc: 0.9173 - cross entropy: 0.0037 - fn: 16.0000 - fp: 4.3462 - loss: 0.0037 - prc: 0.7137 - precision: 0.8832 - recall: 0.6272 - tn: 27599.3086 - tp: 28.3462 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.6464e-04 - accuracy: 0.9992 - auc: 0.9245 - cross entropy: 0.0038 - fn: 32.0980 - fp: 9.1176 - loss: 0.0038 - prc: 0.6972 - precision: 0.8635 - recall: 0.6187 - tn: 53155.0195 - tp: 51.7647"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7359e-04 - accuracy: 0.9992 - auc: 0.9277 - cross entropy: 0.0038 - fn: 48.9605 - fp: 12.9474 - loss: 0.0038 - prc: 0.6997 - precision: 0.8638 - recall: 0.6169 - tn: 78707.7891 - tp: 78.3026"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.7652e-04 - accuracy: 0.9992 - auc: 0.9293 - cross entropy: 0.0038 - fn: 59.1758 - fp: 15.4066 - loss: 0.0038 - prc: 0.7030 - precision: 0.8639 - recall: 0.6167 - tn: 93971.2969 - tp: 94.6923 - val_Brier score: 3.7391e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0022 - val_fn: 12.0000 - val_fp: 6.0000 - val_loss: 0.0022 - val_prc: 0.8934 - val_precision: 0.9211 - val_recall: 0.8537 - val_tn: 45481.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 37/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0015 - accuracy: 0.9985 - auc: 0.9988 - cross entropy: 0.0069 - fn: 1.0000 - fp: 2.0000 - loss: 0.0069 - prc: 0.4169 - precision: 0.6000 - recall: 0.7500 - tn: 2042.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.3572e-04 - accuracy: 0.9992 - auc: 0.9667 - cross entropy: 0.0035 - fn: 15.5200 - fp: 5.4400 - loss: 0.0035 - prc: 0.7624 - precision: 0.8274 - recall: 0.6651 - tn: 26575.4395 - tp: 27.6000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.4164e-04 - accuracy: 0.9992 - auc: 0.9503 - cross entropy: 0.0037 - fn: 32.3469 - fp: 10.0204 - loss: 0.0037 - prc: 0.7452 - precision: 0.8387 - recall: 0.6452 - tn: 51102.9609 - tp: 54.6735"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m74/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.3070e-04 - accuracy: 0.9992 - auc: 0.9461 - cross entropy: 0.0037 - fn: 48.6216 - fp: 14.4054 - loss: 0.0037 - prc: 0.7419 - precision: 0.8451 - recall: 0.6408 - tn: 76654.1094 - tp: 82.8649"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.3074e-04 - accuracy: 0.9992 - auc: 0.9428 - cross entropy: 0.0037 - fn: 60.7802 - fp: 17.3626 - loss: 0.0037 - prc: 0.7377 - precision: 0.8461 - recall: 0.6337 - tn: 93962.8438 - tp: 99.5824 - val_Brier score: 3.6460e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8902 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 38/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 9.9348e-04 - accuracy: 0.9990 - auc: 0.7485 - cross entropy: 0.0063 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0063 - prc: 0.5029 - precision: 1.0000 - recall: 0.5000 - tn: 2044.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5361e-04 - accuracy: 0.9992 - auc: 0.9015 - cross entropy: 0.0040 - fn: 16.9600 - fp: 4.0800 - loss: 0.0040 - prc: 0.7295 - precision: 0.8852 - recall: 0.6146 - tn: 26575.0801 - tp: 27.8800 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.9218e-04 - accuracy: 0.9992 - auc: 0.9140 - cross entropy: 0.0037 - fn: 28.2449 - fp: 8.5918 - loss: 0.0037 - prc: 0.7292 - precision: 0.8722 - recall: 0.6413 - tn: 51109.4688 - tp: 53.6939"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7588e-04 - accuracy: 0.9993 - auc: 0.9179 - cross entropy: 0.0037 - fn: 42.3014 - fp: 12.0548 - loss: 0.0037 - prc: 0.7316 - precision: 0.8740 - recall: 0.6475 - tn: 75640.3438 - tp: 81.3014"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.6683e-04 - accuracy: 0.9993 - auc: 0.9190 - cross entropy: 0.0037 - fn: 52.7912 - fp: 14.1868 - loss: 0.0037 - prc: 0.7344 - precision: 0.8774 - recall: 0.6506 - tn: 93971.1953 - tp: 102.3956 - val_Brier score: 3.6012e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8892 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 39/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 50ms/step - Brier score: 4.8586e-04 - accuracy: 0.9995 - auc: 1.0000 - cross entropy: 0.0028 - fn: 0.0000e+00 - fp: 1.0000 - loss: 0.0028 - prc: 1.0000 - precision: 0.5000 - recall: 1.0000 - tn: 2046.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m27/90\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.9103e-04 - accuracy: 0.9993 - auc: 0.9412 - cross entropy: 0.0031 - fn: 16.2222 - fp: 4.0000 - loss: 0.0031 - prc: 0.7297 - precision: 0.8132 - recall: 0.5892 - tn: 28628.9629 - tp: 22.8148 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.6028e-04 - accuracy: 0.9992 - auc: 0.9266 - cross entropy: 0.0035 - fn: 34.9808 - fp: 8.5192 - loss: 0.0035 - prc: 0.7153 - precision: 0.8348 - recall: 0.5890 - tn: 54178.4219 - tp: 50.0769"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7423e-04 - accuracy: 0.9992 - auc: 0.9241 - cross entropy: 0.0036 - fn: 52.0000 - fp: 13.0513 - loss: 0.0036 - prc: 0.7138 - precision: 0.8422 - recall: 0.5945 - tn: 80753.3594 - tp: 77.5897"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.7595e-04 - accuracy: 0.9992 - auc: 0.9244 - cross entropy: 0.0036 - fn: 59.9890 - fp: 15.4176 - loss: 0.0036 - prc: 0.7161 - precision: 0.8446 - recall: 0.5989 - tn: 93972.8906 - tp: 92.2747 - val_Brier score: 3.6358e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8890 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 40/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 53ms/step - Brier score: 5.6345e-04 - accuracy: 0.9995 - auc: 0.8739 - cross entropy: 0.0039 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0039 - prc: 0.7518 - precision: 1.0000 - recall: 0.7500 - tn: 2044.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.8776e-04 - accuracy: 0.9993 - auc: 0.9355 - cross entropy: 0.0034 - fn: 14.4800 - fp: 6.2400 - loss: 0.0034 - prc: 0.7044 - precision: 0.8295 - recall: 0.6892 - tn: 26576.2793 - tp: 27.0000 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.2979e-04 - accuracy: 0.9993 - auc: 0.9381 - cross entropy: 0.0035 - fn: 31.5510 - fp: 9.5102 - loss: 0.0035 - prc: 0.7157 - precision: 0.8428 - recall: 0.6509 - tn: 51106.9609 - tp: 51.9796"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m72/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3587e-04 - accuracy: 0.9992 - auc: 0.9378 - cross entropy: 0.0036 - fn: 46.0556 - fp: 12.9722 - loss: 0.0036 - prc: 0.7229 - precision: 0.8502 - recall: 0.6443 - tn: 74615.7812 - tp: 77.1944"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.4591e-04 - accuracy: 0.9992 - auc: 0.9358 - cross entropy: 0.0036 - fn: 59.4506 - fp: 16.2747 - loss: 0.0036 - prc: 0.7248 - precision: 0.8518 - recall: 0.6376 - tn: 93967.5078 - tp: 97.3407 - val_Brier score: 3.5726e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 14.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8938 - val_precision: 0.9444 - val_recall: 0.8293 - val_tn: 45483.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 41/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 3.2940e-05 - accuracy: 1.0000 - auc: 1.0000 - cross entropy: 5.5671e-04 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 5.5671e-04 - prc: 1.0000 - precision: 1.0000 - recall: 1.0000 - tn: 2045.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.2216e-04 - accuracy: 0.9993 - auc: 0.9378 - cross entropy: 0.0034 - fn: 14.2917 - fp: 4.7500 - loss: 0.0034 - prc: 0.7519 - precision: 0.8654 - recall: 0.6701 - tn: 25556.0840 - tp: 24.8750 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m46/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3951e-04 - accuracy: 0.9993 - auc: 0.9312 - cross entropy: 0.0035 - fn: 26.7174 - fp: 8.7391 - loss: 0.0035 - prc: 0.7313 - precision: 0.8539 - recall: 0.6543 - tn: 48046.0430 - tp: 46.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m68/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4529e-04 - accuracy: 0.9993 - auc: 0.9304 - cross entropy: 0.0035 - fn: 39.4853 - fp: 12.6912 - loss: 0.0035 - prc: 0.7285 - precision: 0.8529 - recall: 0.6506 - tn: 70533.7188 - tp: 70.1029"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.5670e-04 - accuracy: 0.9993 - auc: 0.9301 - cross entropy: 0.0036 - fn: 54.7582 - fp: 16.5494 - loss: 0.0036 - prc: 0.7288 - precision: 0.8547 - recall: 0.6463 - tn: 93973.3281 - tp: 95.9341 - val_Brier score: 3.5593e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8933 - val_precision: 0.9459 - val_recall: 0.8537 - val_tn: 45483.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 42/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 6.6164e-04 - accuracy: 0.9995 - auc: 0.9998 - cross entropy: 0.0030 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0030 - prc: 0.9548 - precision: 1.0000 - recall: 0.8571 - tn: 2041.0000 - tp: 6.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.6482e-04 - accuracy: 0.9992 - auc: 0.9313 - cross entropy: 0.0040 - fn: 16.4800 - fp: 6.4000 - loss: 0.0040 - prc: 0.7360 - precision: 0.8520 - recall: 0.6956 - tn: 26568.7598 - tp: 32.3600 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.6733e-04 - accuracy: 0.9992 - auc: 0.9195 - cross entropy: 0.0042 - fn: 33.6327 - fp: 9.4286 - loss: 0.0042 - prc: 0.7152 - precision: 0.8589 - recall: 0.6570 - tn: 51100.2656 - tp: 56.6735"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5162e-04 - accuracy: 0.9992 - auc: 0.9176 - cross entropy: 0.0041 - fn: 50.0137 - fp: 12.2055 - loss: 0.0041 - prc: 0.7145 - precision: 0.8651 - recall: 0.6401 - tn: 75633.6953 - tp: 80.0822"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 7.4028e-04 - accuracy: 0.9992 - auc: 0.9187 - cross entropy: 0.0040 - fn: 61.0769 - fp: 15.6593 - loss: 0.0040 - prc: 0.7178 - precision: 0.8634 - recall: 0.6371 - tn: 93964.6172 - tp: 99.2198 - val_Brier score: 3.5573e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 15.0000 - val_fp: 3.0000 - val_loss: 0.0021 - val_prc: 0.8955 - val_precision: 0.9571 - val_recall: 0.8171 - val_tn: 45484.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 43/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 53ms/step - Brier score: 1.9975e-04 - accuracy: 1.0000 - auc: 1.0000 - cross entropy: 0.0010 - fn: 0.0000e+00 - fp: 0.0000e+00 - loss: 0.0010 - prc: 1.0000 - precision: 1.0000 - recall: 1.0000 - tn: 2043.0000 - tp: 5.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.9696e-04 - accuracy: 0.9991 - auc: 0.9284 - cross entropy: 0.0040 - fn: 22.4000 - fp: 2.8400 - loss: 0.0040 - prc: 0.7590 - precision: 0.9181 - recall: 0.5717 - tn: 26569.8398 - tp: 28.9200 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.6424e-04 - accuracy: 0.9991 - auc: 0.9285 - cross entropy: 0.0039 - fn: 39.6327 - fp: 5.8367 - loss: 0.0039 - prc: 0.7504 - precision: 0.9108 - recall: 0.5766 - tn: 51100.4062 - tp: 54.1224"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5028e-04 - accuracy: 0.9991 - auc: 0.9284 - cross entropy: 0.0039 - fn: 55.7397 - fp: 10.1370 - loss: 0.0039 - prc: 0.7412 - precision: 0.8976 - recall: 0.5806 - tn: 75632.0000 - tp: 78.1233"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 7.4173e-04 - accuracy: 0.9991 - auc: 0.9276 - cross entropy: 0.0039 - fn: 67.1099 - fp: 13.5165 - loss: 0.0039 - prc: 0.7369 - precision: 0.8910 - recall: 0.5853 - tn: 93963.0469 - tp: 96.9011 - val_Brier score: 3.5516e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 15.0000 - val_fp: 3.0000 - val_loss: 0.0021 - val_prc: 0.8967 - val_precision: 0.9571 - val_recall: 0.8171 - val_tn: 45484.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 44/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 4.9890e-04 - accuracy: 0.9995 - auc: 0.9996 - cross entropy: 0.0048 - fn: 0.0000e+00 - fp: 1.0000 - loss: 0.0048 - prc: 0.7280 - precision: 0.8333 - recall: 1.0000 - tn: 2042.0000 - tp: 5.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7472e-04 - accuracy: 0.9992 - auc: 0.9010 - cross entropy: 0.0044 - fn: 17.1200 - fp: 5.2400 - loss: 0.0044 - prc: 0.6875 - precision: 0.8541 - recall: 0.6832 - tn: 26571.4395 - tp: 30.2000 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.9709e-04 - accuracy: 0.9992 - auc: 0.9006 - cross entropy: 0.0043 - fn: 34.7551 - fp: 8.5714 - loss: 0.0043 - prc: 0.6854 - precision: 0.8603 - recall: 0.6428 - tn: 51102.4297 - tp: 54.2449"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.9325e-04 - accuracy: 0.9992 - auc: 0.9046 - cross entropy: 0.0042 - fn: 50.2329 - fp: 12.1096 - loss: 0.0042 - prc: 0.6875 - precision: 0.8626 - recall: 0.6316 - tn: 75635.1797 - tp: 78.4795"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.8514e-04 - accuracy: 0.9992 - auc: 0.9083 - cross entropy: 0.0041 - fn: 61.3626 - fp: 14.4176 - loss: 0.0041 - prc: 0.6952 - precision: 0.8665 - recall: 0.6305 - tn: 93966.5938 - tp: 98.1978 - val_Brier score: 3.5625e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 14.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8940 - val_precision: 0.9444 - val_recall: 0.8293 - val_tn: 45483.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 45/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0011 - accuracy: 0.9990 - auc: 0.7422 - cross entropy: 0.0062 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0062 - prc: 0.0130 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2046.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5843e-04 - accuracy: 0.9993 - auc: 0.9258 - cross entropy: 0.0036 - fn: 15.1538 - fp: 3.7692 - loss: 0.0036 - prc: 0.7461 - precision: 0.8917 - recall: 0.6582 - tn: 27594.5000 - tp: 34.5769 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4721e-04 - accuracy: 0.9993 - auc: 0.9353 - cross entropy: 0.0034 - fn: 28.1400 - fp: 9.5400 - loss: 0.0034 - prc: 0.7657 - precision: 0.8730 - recall: 0.6715 - tn: 52124.6992 - tp: 61.6200"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m75/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5071e-04 - accuracy: 0.9993 - auc: 0.9350 - cross entropy: 0.0035 - fn: 43.2133 - fp: 14.3200 - loss: 0.0035 - prc: 0.7606 - precision: 0.8664 - recall: 0.6657 - tn: 77679.2656 - tp: 87.2000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.5736e-04 - accuracy: 0.9993 - auc: 0.9347 - cross entropy: 0.0035 - fn: 53.7363 - fp: 17.3407 - loss: 0.0035 - prc: 0.7572 - precision: 0.8641 - recall: 0.6611 - tn: 93965.4609 - tp: 104.0330 - val_Brier score: 3.5624e-04 - val_accuracy: 0.9996 - val_auc: 0.9693 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8999 - val_precision: 0.9459 - val_recall: 0.8537 - val_tn: 45483.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 46/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 7.1167e-04 - accuracy: 0.9990 - auc: 0.7477 - cross entropy: 0.0036 - fn: 1.0000 - fp: 1.0000 - loss: 0.0036 - prc: 0.5014 - precision: 0.5000 - recall: 0.5000 - tn: 2045.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4503e-04 - accuracy: 0.9992 - auc: 0.9394 - cross entropy: 0.0030 - fn: 18.0769 - fp: 4.7692 - loss: 0.0030 - prc: 0.8102 - precision: 0.8532 - recall: 0.6227 - tn: 27596.4609 - tp: 28.6923"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3563e-04 - accuracy: 0.9992 - auc: 0.9371 - cross entropy: 0.0031 - fn: 33.6275 - fp: 9.6863 - loss: 0.0031 - prc: 0.7885 - precision: 0.8459 - recall: 0.6167 - tn: 53151.7070 - tp: 52.9804"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m72/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3631e-04 - accuracy: 0.9992 - auc: 0.9347 - cross entropy: 0.0032 - fn: 47.0278 - fp: 13.0139 - loss: 0.0032 - prc: 0.7764 - precision: 0.8490 - recall: 0.6148 - tn: 74618.1094 - tp: 73.8472"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.4475e-04 - accuracy: 0.9992 - auc: 0.9327 - cross entropy: 0.0034 - fn: 59.7473 - fp: 16.5824 - loss: 0.0034 - prc: 0.7666 - precision: 0.8494 - recall: 0.6148 - tn: 93969.7031 - tp: 94.5385 - val_Brier score: 3.5600e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 14.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8953 - val_precision: 0.9315 - val_recall: 0.8293 - val_tn: 45482.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 47/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 9.6165e-04 - accuracy: 0.9990 - auc: 0.9982 - cross entropy: 0.0050 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0050 - prc: 0.5182 - precision: 1.0000 - recall: 0.3333 - tn: 2045.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.2017e-04 - accuracy: 0.9992 - auc: 0.9740 - cross entropy: 0.0031 - fn: 14.2800 - fp: 5.8000 - loss: 0.0031 - prc: 0.7938 - precision: 0.8818 - recall: 0.7005 - tn: 26567.5195 - tp: 36.4000 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m48/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4295e-04 - accuracy: 0.9992 - auc: 0.9646 - cross entropy: 0.0033 - fn: 29.8333 - fp: 10.0208 - loss: 0.0033 - prc: 0.7895 - precision: 0.8732 - recall: 0.6854 - tn: 50072.2500 - tp: 63.8958"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m71/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.4603e-04 - accuracy: 0.9992 - auc: 0.9575 - cross entropy: 0.0034 - fn: 44.4930 - fp: 12.5634 - loss: 0.0034 - prc: 0.7777 - precision: 0.8774 - recall: 0.6741 - tn: 73582.5078 - tp: 88.4366"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.4711e-04 - accuracy: 0.9992 - auc: 0.9535 - cross entropy: 0.0034 - fn: 56.6044 - fp: 15.2637 - loss: 0.0034 - prc: 0.7703 - precision: 0.8783 - recall: 0.6687 - tn: 93959.1797 - tp: 109.5275 - val_Brier score: 3.5447e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 14.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8957 - val_precision: 0.9315 - val_recall: 0.8293 - val_tn: 45482.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 48/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 4.8799e-04 - accuracy: 0.9995 - auc: 0.4944 - cross entropy: 0.0035 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0035 - prc: 4.6865e-04 - precision: 0.0000e+00 - recall: 0.0000e+00 - tn: 2047.0000 - tp: 0.0000e+00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.4587e-04 - accuracy: 0.9991 - auc: 0.9048 - cross entropy: 0.0037 - fn: 18.6250 - fp: 4.7083 - loss: 0.0037 - prc: 0.6617 - precision: 0.7545 - recall: 0.4955 - tn: 25553.7500 - tp: 22.9167 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m46/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.1121e-04 - accuracy: 0.9992 - auc: 0.9238 - cross entropy: 0.0035 - fn: 31.6739 - fp: 7.8043 - loss: 0.0035 - prc: 0.7013 - precision: 0.8027 - recall: 0.5435 - tn: 48044.0664 - tp: 44.4565"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m69/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.0187e-04 - accuracy: 0.9992 - auc: 0.9278 - cross entropy: 0.0035 - fn: 47.2029 - fp: 10.2319 - loss: 0.0035 - prc: 0.7134 - precision: 0.8286 - recall: 0.5577 - tn: 71556.0000 - tp: 66.5652"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 7.0048e-04 - accuracy: 0.9992 - auc: 0.9278 - cross entropy: 0.0035 - fn: 62.0110 - fp: 13.0659 - loss: 0.0035 - prc: 0.7176 - precision: 0.8421 - recall: 0.5699 - tn: 93974.2891 - tp: 91.2088 - val_Brier score: 3.5628e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8904 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 49/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 3.8661e-04 - accuracy: 0.9995 - auc: 1.0000 - cross entropy: 0.0014 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0014 - prc: 1.0000 - precision: 1.0000 - recall: 0.5000 - tn: 2046.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 5.5717e-04 - accuracy: 0.9993 - auc: 0.9680 - cross entropy: 0.0030 - fn: 14.8750 - fp: 4.0833 - loss: 0.0030 - prc: 0.7944 - precision: 0.8751 - recall: 0.6156 - tn: 25555.7500 - tp: 25.2917 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5897e-04 - accuracy: 0.9992 - auc: 0.9527 - cross entropy: 0.0035 - fn: 33.6596 - fp: 9.4681 - loss: 0.0035 - prc: 0.7572 - precision: 0.8571 - recall: 0.6046 - tn: 49058.5117 - tp: 50.3617"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m70/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8675e-04 - accuracy: 0.9992 - auc: 0.9462 - cross entropy: 0.0036 - fn: 49.8143 - fp: 14.9143 - loss: 0.0036 - prc: 0.7417 - precision: 0.8443 - recall: 0.5989 - tn: 72566.6875 - tp: 72.5857"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.9120e-04 - accuracy: 0.9992 - auc: 0.9443 - cross entropy: 0.0036 - fn: 63.6813 - fp: 18.6593 - loss: 0.0036 - prc: 0.7408 - precision: 0.8440 - recall: 0.5999 - tn: 93963.7656 - tp: 94.4615 - val_Brier score: 3.5756e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8908 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 50/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 8.6887e-04 - accuracy: 0.9990 - auc: 0.7485 - cross entropy: 0.0045 - fn: 1.0000 - fp: 1.0000 - loss: 0.0045 - prc: 0.5015 - precision: 0.5000 - recall: 0.5000 - tn: 2045.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 8.1906e-04 - accuracy: 0.9991 - auc: 0.8982 - cross entropy: 0.0047 - fn: 17.7083 - fp: 5.7917 - loss: 0.0047 - prc: 0.6527 - precision: 0.8001 - recall: 0.5872 - tn: 25548.8750 - tp: 27.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m48/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.8306e-04 - accuracy: 0.9991 - auc: 0.9049 - cross entropy: 0.0044 - fn: 34.4792 - fp: 9.1458 - loss: 0.0044 - prc: 0.6806 - precision: 0.8364 - recall: 0.6062 - tn: 50075.8945 - tp: 56.4792"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m71/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.5373e-04 - accuracy: 0.9991 - auc: 0.9084 - cross entropy: 0.0043 - fn: 48.2254 - fp: 12.6620 - loss: 0.0043 - prc: 0.6955 - precision: 0.8484 - recall: 0.6172 - tn: 73584.4531 - tp: 82.6620"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 7.3006e-04 - accuracy: 0.9992 - auc: 0.9119 - cross entropy: 0.0041 - fn: 58.7473 - fp: 15.9670 - loss: 0.0041 - prc: 0.7054 - precision: 0.8526 - recall: 0.6254 - tn: 93961.4062 - tp: 104.4505 - val_Brier score: 3.5366e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 15.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8914 - val_precision: 0.9437 - val_recall: 0.8171 - val_tn: 45483.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 51/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0015 - accuracy: 0.9985 - auc: 0.7981 - cross entropy: 0.0133 - fn: 3.0000 - fp: 0.0000e+00 - loss: 0.0133 - prc: 0.5724 - precision: 1.0000 - recall: 0.4000 - tn: 2043.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.4388e-04 - accuracy: 0.9992 - auc: 0.8817 - cross entropy: 0.0052 - fn: 18.2400 - fp: 1.0000 - loss: 0.0052 - prc: 0.6781 - precision: 0.9641 - recall: 0.4888 - tn: 26585.8008 - tp: 18.9600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m48/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8357e-04 - accuracy: 0.9993 - auc: 0.9039 - cross entropy: 0.0044 - fn: 30.6250 - fp: 4.3542 - loss: 0.0044 - prc: 0.7121 - precision: 0.9371 - recall: 0.5547 - tn: 50095.2500 - tp: 45.7708"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m71/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8143e-04 - accuracy: 0.9992 - auc: 0.9128 - cross entropy: 0.0041 - fn: 45.0704 - fp: 9.3239 - loss: 0.0041 - prc: 0.7248 - precision: 0.9156 - recall: 0.5813 - tn: 73599.8906 - tp: 73.7183"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.7601e-04 - accuracy: 0.9992 - auc: 0.9166 - cross entropy: 0.0040 - fn: 56.8681 - fp: 12.8901 - loss: 0.0040 - prc: 0.7306 - precision: 0.9066 - recall: 0.5950 - tn: 93974.1016 - tp: 96.7143 - val_Brier score: 3.5455e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8962 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 52/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 5.3560e-04 - accuracy: 0.9995 - auc: 0.9998 - cross entropy: 0.0023 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0023 - prc: 0.9088 - precision: 1.0000 - recall: 0.7500 - tn: 2044.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3493e-04 - accuracy: 0.9993 - auc: 0.9690 - cross entropy: 0.0033 - fn: 14.4000 - fp: 4.5600 - loss: 0.0033 - prc: 0.7922 - precision: 0.8929 - recall: 0.6950 - tn: 26573.7207 - tp: 31.3200 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.6107e-04 - accuracy: 0.9993 - auc: 0.9579 - cross entropy: 0.0034 - fn: 29.3673 - fp: 8.7755 - loss: 0.0034 - prc: 0.7736 - precision: 0.8832 - recall: 0.6827 - tn: 51101.2227 - tp: 60.6327"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m73/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.8254e-04 - accuracy: 0.9992 - auc: 0.9525 - cross entropy: 0.0036 - fn: 45.7671 - fp: 13.6301 - loss: 0.0036 - prc: 0.7617 - precision: 0.8752 - recall: 0.6698 - tn: 75629.0703 - tp: 87.5342"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 6.8761e-04 - accuracy: 0.9992 - auc: 0.9491 - cross entropy: 0.0036 - fn: 57.3626 - fp: 16.6703 - loss: 0.0036 - prc: 0.7558 - precision: 0.8728 - recall: 0.6633 - tn: 93960.0781 - tp: 106.4615 - val_Brier score: 3.5794e-04 - val_accuracy: 0.9996 - val_auc: 0.9510 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8856 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 53/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 5.6046e-04 - accuracy: 0.9995 - auc: 0.9998 - cross entropy: 0.0025 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0025 - prc: 0.9088 - precision: 1.0000 - recall: 0.7500 - tn: 2044.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.3008e-04 - accuracy: 0.9993 - auc: 0.9453 - cross entropy: 0.0038 - fn: 15.1667 - fp: 3.5833 - loss: 0.0038 - prc: 0.7459 - precision: 0.9042 - recall: 0.6515 - tn: 25553.2500 - tp: 28.0000 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.5961e-04 - accuracy: 0.9993 - auc: 0.9362 - cross entropy: 0.0039 - fn: 29.4255 - fp: 8.5319 - loss: 0.0039 - prc: 0.7352 - precision: 0.8816 - recall: 0.6517 - tn: 49059.4883 - tp: 54.5532"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m70/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7387e-04 - accuracy: 0.9992 - auc: 0.9338 - cross entropy: 0.0039 - fn: 44.8429 - fp: 12.6714 - loss: 0.0039 - prc: 0.7340 - precision: 0.8760 - recall: 0.6475 - tn: 72565.3750 - tp: 81.1143"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.7372e-04 - accuracy: 0.9992 - auc: 0.9337 - cross entropy: 0.0039 - fn: 57.6483 - fp: 16.1758 - loss: 0.0039 - prc: 0.7352 - precision: 0.8740 - recall: 0.6468 - tn: 93962.3203 - tp: 104.4286 - val_Brier score: 3.5337e-04 - val_accuracy: 0.9996 - val_auc: 0.9510 - val_cross entropy: 0.0021 - val_fn: 15.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8867 - val_precision: 0.9437 - val_recall: 0.8171 - val_tn: 45483.0000 - val_tp: 67.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 54/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 9.1353e-04 - accuracy: 0.9990 - auc: 0.8323 - cross entropy: 0.0048 - fn: 2.0000 - fp: 0.0000e+00 - loss: 0.0048 - prc: 0.6684 - precision: 1.0000 - recall: 0.3333 - tn: 2045.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.0211e-04 - accuracy: 0.9992 - auc: 0.9181 - cross entropy: 0.0038 - fn: 17.5600 - fp: 2.4000 - loss: 0.0038 - prc: 0.7611 - precision: 0.9446 - recall: 0.6143 - tn: 26571.6797 - tp: 32.3600 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7775e-04 - accuracy: 0.9993 - auc: 0.9281 - cross entropy: 0.0036 - fn: 31.1224 - fp: 6.5306 - loss: 0.0036 - prc: 0.7630 - precision: 0.9158 - recall: 0.6319 - tn: 51104.7344 - tp: 57.6122"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m72/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7356e-04 - accuracy: 0.9993 - auc: 0.9293 - cross entropy: 0.0036 - fn: 45.2917 - fp: 10.7222 - loss: 0.0036 - prc: 0.7580 - precision: 0.9022 - recall: 0.6350 - tn: 74613.7891 - tp: 82.1944"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 6.7745e-04 - accuracy: 0.9992 - auc: 0.9296 - cross entropy: 0.0036 - fn: 57.5275 - fp: 14.4725 - loss: 0.0036 - prc: 0.7534 - precision: 0.8939 - recall: 0.6348 - tn: 93965.9453 - tp: 102.6264 - val_Brier score: 3.5481e-04 - val_accuracy: 0.9996 - val_auc: 0.9571 - val_cross entropy: 0.0021 - val_fn: 14.0000 - val_fp: 4.0000 - val_loss: 0.0021 - val_prc: 0.8912 - val_precision: 0.9444 - val_recall: 0.8293 - val_tn: 45483.0000 - val_tp: 68.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 55/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 4.8868e-04 - accuracy: 0.9995 - auc: 0.8739 - cross entropy: 0.0033 - fn: 1.0000 - fp: 0.0000e+00 - loss: 0.0033 - prc: 0.7518 - precision: 1.0000 - recall: 0.7500 - tn: 2044.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.7538e-04 - accuracy: 0.9992 - auc: 0.9112 - cross entropy: 0.0038 - fn: 18.3200 - fp: 3.0400 - loss: 0.0038 - prc: 0.7585 - precision: 0.8987 - recall: 0.6156 - tn: 26575.6797 - tp: 26.9600 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 6.9006e-04 - accuracy: 0.9992 - auc: 0.9207 - cross entropy: 0.0038 - fn: 35.7143 - fp: 6.4694 - loss: 0.0038 - prc: 0.7506 - precision: 0.8925 - recall: 0.6029 - tn: 51105.9609 - tp: 51.8571"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m74/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 7.0054e-04 - accuracy: 0.9992 - auc: 0.9212 - cross entropy: 0.0038 - fn: 52.6486 - fp: 10.7568 - loss: 0.0038 - prc: 0.7417 - precision: 0.8853 - recall: 0.6022 - tn: 76658.5703 - tp: 78.0270"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 7.0387e-04 - accuracy: 0.9992 - auc: 0.9224 - cross entropy: 0.0038 - fn: 64.3626 - fp: 13.1429 - loss: 0.0038 - prc: 0.7406 - precision: 0.8846 - recall: 0.6024 - tn: 93966.8203 - tp: 96.2418 - val_Brier score: 3.6211e-04 - val_accuracy: 0.9996 - val_auc: 0.9632 - val_cross entropy: 0.0021 - val_fn: 12.0000 - val_fp: 5.0000 - val_loss: 0.0021 - val_prc: 0.8954 - val_precision: 0.9333 - val_recall: 0.8537 - val_tn: 45482.0000 - val_tp: 70.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 55: early stopping\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Restoring model weights from the end of the best epoch: 45.\n"
]
}
],
"source": [
"model = make_model()\n",
"model.load_weights(initial_weights)\n",
"baseline_history = model.fit(\n",
" train_features,\n",
" train_labels,\n",
" batch_size=BATCH_SIZE,\n",
" epochs=EPOCHS,\n",
" callbacks=[early_stopping()],\n",
" validation_data=(val_features, val_labels))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "iSaDBYU9xtP6"
},
"source": [
"### Check training history\n",
"\n",
"In this section, you will produce plots of your model's accuracy and loss on the training and validation set. These are useful to check for overfitting, which you can learn more about in the [Overfit and underfit](https://www.tensorflow.org/tutorials/keras/overfit_and_underfit) tutorial.\n",
"\n",
"Additionally, you can produce these plots for any of the metrics you created above. False negatives are included as an example."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:08.461322Z",
"iopub.status.busy": "2024-08-20T01:25:08.461057Z",
"iopub.status.idle": "2024-08-20T01:25:08.467255Z",
"shell.execute_reply": "2024-08-20T01:25:08.466519Z"
},
"id": "WTSkhT1jyGu6"
},
"outputs": [],
"source": [
"def plot_metrics(history):\n",
" metrics = ['loss', 'prc', 'precision', 'recall']\n",
" for n, metric in enumerate(metrics):\n",
" name = metric.replace(\"_\",\" \").capitalize()\n",
" plt.subplot(2,2,n+1)\n",
" plt.plot(history.epoch, history.history[metric], color=colors[0], label='Train')\n",
" plt.plot(history.epoch, history.history['val_'+metric],\n",
" color=colors[0], linestyle=\"--\", label='Val')\n",
" plt.xlabel('Epoch')\n",
" plt.ylabel(name)\n",
" if metric == 'loss':\n",
" plt.ylim([0, plt.ylim()[1]])\n",
" elif metric == 'auc':\n",
" plt.ylim([0.8,1])\n",
" else:\n",
" plt.ylim([0,1])\n",
"\n",
" plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:08.470194Z",
"iopub.status.busy": "2024-08-20T01:25:08.469935Z",
"iopub.status.idle": "2024-08-20T01:25:08.941300Z",
"shell.execute_reply": "2024-08-20T01:25:08.940644Z"
},
"id": "u6LReDsqlZlk"
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_metrics(baseline_history)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "UCa4iWo6WDKR"
},
"source": [
"Note: That the validation curve generally performs better than the training curve. This is mainly caused by the fact that the dropout layer is not active when evaluating the model."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "aJC1booryouo"
},
"source": [
"### Evaluate metrics\n",
"\n",
"You can use a [confusion matrix](https://developers.google.com/machine-learning/glossary/#confusion_matrix) to summarize the actual vs. predicted labels, where the X axis is the predicted label and the Y axis is the actual label:"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:08.946137Z",
"iopub.status.busy": "2024-08-20T01:25:08.945814Z",
"iopub.status.idle": "2024-08-20T01:25:09.719092Z",
"shell.execute_reply": "2024-08-20T01:25:09.718285Z"
},
"id": "aNS796IJKrev"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m14s\u001b[0m 168ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/28\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 41ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m28/28\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 6ms/step "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m28/28\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 6ms/step\n"
]
}
],
"source": [
"train_predictions_baseline = model.predict(train_features, batch_size=BATCH_SIZE)\n",
"test_predictions_baseline = model.predict(test_features, batch_size=BATCH_SIZE)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:09.722827Z",
"iopub.status.busy": "2024-08-20T01:25:09.722541Z",
"iopub.status.idle": "2024-08-20T01:25:09.727974Z",
"shell.execute_reply": "2024-08-20T01:25:09.727364Z"
},
"id": "MVWBGfADwbWI"
},
"outputs": [],
"source": [
"def plot_cm(labels, predictions, threshold=0.5):\n",
" cm = confusion_matrix(labels, predictions > threshold)\n",
" plt.figure(figsize=(5,5))\n",
" sns.heatmap(cm, annot=True, fmt=\"d\")\n",
" plt.title('Confusion matrix @{:.2f}'.format(threshold))\n",
" plt.ylabel('Actual label')\n",
" plt.xlabel('Predicted label')\n",
"\n",
" print('Legitimate Transactions Detected (True Negatives): ', cm[0][0])\n",
" print('Legitimate Transactions Incorrectly Detected (False Positives): ', cm[0][1])\n",
" print('Fraudulent Transactions Missed (False Negatives): ', cm[1][0])\n",
" print('Fraudulent Transactions Detected (True Positives): ', cm[1][1])\n",
" print('Total Fraudulent Transactions: ', np.sum(cm[1]))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nOTjD5Z5Wp1U"
},
"source": [
"Evaluate your model on the test dataset and display the results for the metrics you created above:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:09.731099Z",
"iopub.status.busy": "2024-08-20T01:25:09.730841Z",
"iopub.status.idle": "2024-08-20T01:25:11.082690Z",
"shell.execute_reply": "2024-08-20T01:25:11.082035Z"
},
"id": "poh_hZngt2_9"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"loss : 0.002663512947037816\n",
"compile_metrics : 0.002663512947037816\n",
"\n",
"Legitimate Transactions Detected (True Negatives): 56854\n",
"Legitimate Transactions Incorrectly Detected (False Positives): 6\n",
"Fraudulent Transactions Missed (False Negatives): 21\n",
"Fraudulent Transactions Detected (True Positives): 81\n",
"Total Fraudulent Transactions: 102\n"
]
},
{
"data": {
"image/png": 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//FLvBvfCwkIxY8YM4e7uLipXrixq16792IctPKhDhw6iQ4cO0vdH3eIixL2HKDRt2lSo1WrRsGFD8e2335a6xSU+Pl706tVLuLi4CLVaLVxcXMTgwYPF33//XeoYDz5s4ZdffhHt2rUTlpaWwtbWVvTo0eORD1t48Baakgcc3P/Qg4cpedjCgx71+wGg9xSdmzdvihEjRojq1asLGxsb4e/vL86ePfvQW1NWrlwp6tatK8zNzR/6sIWHuX+cK1euCDs7O9GjR49S/fr06SOsra3FhQsXHnu+gYGBwsfHR2i1WqktJSVFHDhwQNy8eVPcvXtXJCQkiOzs7EeOcePGDREUFCSqVasmrKysRIcOHcSRI0ceGvv9t0HdvHlTDB06VHh4eAgrKyuh0WhEkyZNxOzZs0VBQUGp/YuLi8Xs2bOFm5ubUKvVokmTJuLbb7997PkRlSeVEGVYZUFEL6ysrCx4e3ujadOmWL9+vbQC/H7FxcXYunUr+vfvb4IIiZ5fTKJEhL///hsBAQHIzc3F2LFj8cYbb8DFxQW5ubn47bffsGTJEqSlpeHo0aMPvQ2KSKmYRIkIwL0VsfPnz8eqVav0blmpUqUKhgwZgvDwcNSsWdOEERI9f5hEiUiPEALnz59HWloabG1t0bhxY6jValOHRfRcYhIlIiIyEu8TJSIiMhKTKBERkZGYRImIiIz0Qj6xqDBLvtd2ET2OpUv7J3cikkFRwT+yjifn35OVq9eVbayK5oVMokRE9AQ6+d6YpGQs5xIRERmJM1EiIiUSZX+3LT0akygRkRIZ8IJ4ejSWc4mIiIzEmSgRkQIJlnNlwSRKRKRELOfKguVcIiIiI3EmSkSkRCznyoJJlIhIifiwBVmwnEtERGQkzkSJiJSI5VxZMIkSESkRV+fKguVcIiIiI3EmSkSkQHzYgjyYRImIlIjlXFmwnEtERGQkzkSJiJSI5VxZMIkSESkRH7YgC5ZziYiIjMSZKBGRErGcKwsmUSIiJeLqXFmwnEtERGQkzkSJiJSI5VxZMIkSESkRy7myYDmXiIjISJyJEhEpkBC8T1QOTKJERErEa6KyYDmXiIjISJyJEhEpERcWyYJJlIhIiVjOlQXLuUREREbiTJSISIn4FhdZMIkSESkRy7myYDmXiIjISJyJEhEpEVfnyoJJlIhIiVjOlQXLuUREREbiTJSISIlYzpUFkygRkRIxicqC5VwiIiIjMYkSESmQEMWyfQwxffp0qFQqvU+jRo2k7fn5+QgODka1atVgY2ODfv36IT09XW+M1NRUBAQEwMrKCo6Ojpg4cSKKior0+uzduxctW7aERqOBh4cHoqOjS8WydOlS1KlTBxYWFvDx8cHhw4cNOheASZSISJl0Ovk+BmrSpAmuX78ufX777TdpW2hoKLZv347Nmzdj3759uHbtGvr27SttLy4uRkBAAAoKCnDw4EGsWbMG0dHRCA8Pl/pcvHgRAQEB6NSpE5KSkjBhwgSMGjUKu3fvlvps3LgRYWFhmDZtGo4ePYoWLVrA398fGRkZBp2LSgghDP4NPOcKsy6YOgRSCEuX9qYOgRSiqOAfWce7u/cb2cay7DiyzH2nT5+Obdu2ISkpqdS2nJwc1KhRA+vWrUP//v0BAGfPnkXjxo2RkJCAtm3bYteuXejevTuuXbsGJycnAMDy5csxefJkZGZmQq1WY/LkyYiJicHJkyelsQcNGoTs7GzExsYCAHx8fNC6dWssWbIEAKDT6VC7dm2EhIRgypQpZT4fzkSJiJRI6GT7aLVa5Obm6n20Wu0jD33u3Dm4uLigbt26GDJkCFJTUwEAiYmJKCwshJ+fn9S3UaNGcHV1RUJCAgAgISEBzZo1kxIoAPj7+yM3NxenTp2S+tw/RkmfkjEKCgqQmJio18fMzAx+fn5Sn7JiEiUiUiIZy7kRERGws7PT+0RERDz0sD4+PoiOjkZsbCyWLVuGixcvon379rh16xbS0tKgVqthb2+vt4+TkxPS0tIAAGlpaXoJtGR7ybbH9cnNzcXdu3eRlZWF4uLih/YpGaOseIsLERE9lalTpyIsLEyvTaPRPLRv165dpZ+bN28OHx8fuLm5YdOmTbC0tCzXOMsDZ6JEREokYzlXo9HA1tZW7/OoJPoge3t7NGjQAOfPn4ezszMKCgqQnZ2t1yc9PR3Ozs4AAGdn51KrdUu+P6mPra0tLC0tUb16dZibmz+0T8kYZcUkSkSkRCZcnXu/27dvIyUlBTVr1oS3tzcqV66M+Ph4aXtycjJSU1Ph6+sLAPD19cWJEyf0VtHGxcXB1tYWnp6eUp/7xyjpUzKGWq2Gt7e3Xh+dTof4+HipT1kxiRIR0TPz4YcfYt++fbh06RIOHjyIPn36wNzcHIMHD4adnR2CgoIQFhaGX3/9FYmJiRgxYgR8fX3Rtm1bAEDnzp3h6emJYcOG4fjx49i9ezc++eQTBAcHS7Pf0aNH48KFC5g0aRLOnj2LqKgobNq0CaGhoVIcYWFhWLlyJdasWYMzZ85gzJgxyMvLw4gRIww6H14TJSJSIhO9xeXq1asYPHgw/v33X9SoUQOvvPIKDh06hBo1agAAFi5cCDMzM/Tr1w9arRb+/v6IioqS9jc3N8eOHTswZswY+Pr6wtraGoGBgZg5c6bUx93dHTExMQgNDcXixYtRq1YtrFq1Cv7+/lKfgQMHIjMzE+Hh4UhLS4OXlxdiY2NLLTZ6Et4nSvQUeJ8oPSuy3ye6K1K2sSy7jpNtrIqG5VwiIiIjsZxLRKREfIuLLJhEiYiUyETXRF80LOcSEREZiTNRIiIlYjlXFkyiRERKxHKuLFjOJSIiMhJnokRESsRyriyYRImIlIjlXFmwnEtERGQkzkSJiJSI5VxZMIkSESkRk6gsWM4lIiIyEmeiRERK9OK9wMskmESJiJSI5VxZsJxLRERkJM5EiYiUiDNRWTCJEhEpER+2IAuWc4mIiIzEmSgRkRKxnCsLJlEiIiXiLS6yYDmXiIjISJyJEhEpEcu5smASJSJSIiZRWbCcS0REZCTORImIlIj3icqCSZSISIGEjqtz5cByLhERkZE4EyUiUiIuLJIFkygRkRLxmqgsWM4lIiIyEmeiRERKxIVFsmASJSJSIl4TlQXLuUREREbiTJSISIk4E5UFkygRkRLxVWiyYDmXiIjISJyJEhEpEcu5smASraCWfv0tln3znV6bu2stbF+/UvqedPIMIr9agxOnz8LMzAyN6tfDVws/h4VGAwC4lHoVC5Z+jWMnTqOwsBANPNwRMupttPFuIY3RtF3XUseeN2Myuvl1LNV+9K9TGDF2Ejzc6+D7NUtlOlN6Ubi4OCNi9kfo4v8arKwscD7lEkaNCkPi0b9MHZoy8RYXWTCJVmAe7m5YtXi29N3c3Fz6OenkGYwO+wSjhg3ER6FjYG5ujuTzF2CmUkl9gidNh2stF3wdOQcWGjXWbtqG4EnTsGvTN6hezUHq9/lHYXilrbf0vYqNTalYcm/dxkef/Qc+3l7490a2zGdKFZ29vR32792GvfsOonuPocjM+hf1PdxxMzvH1KERPRUm0QrM3NxcL9ndb97irzCkfy+MGjZAanN3qyX9fDM7B5ev/IOZUyagoYc7ACB09Ahs+GEHzl24rDdulSrWjzxOiZnzv0TAG51gZm6GPfsTnua06AU0aeL7uHr1Gka9Eya1Xbp0xYQRER/7Jw+TLizKysrCvHnz0KdPH/j6+sLX1xd9+vTB/PnzkZmZacrQKoTUq/+gU88h6PLmCEyePhfX0zIAAP/ezMZfp5PhUNUOQ94Lw6vdB2N48EQcPX5S2tfezhburrXwU2w87tzNR1FRMTb9uBMOVe3h2dBD7zizFkThlW4DMWjUePywYzfEA6v6tsb8jKvX0jBm5JDyP2mqkLp374zExL+wYf1XuHb1OI4c3o2gkW+ZOixl0wn5PgpmspnokSNH4O/vDysrK/j5+aFBgwYAgPT0dERGRmLOnDnYvXs3WrVq9dhxtFottFqtXpuZVgvN/133e1E192yIzz/+AHVcayHr3xuI+uY7vP3+RGxbuwxX/7kOAIj65jt8OHYUGtWvi592xSNo/FRsW7scbrVfgkqlwsrFszFuymfweaMvzMxUcLC3x1dffAY72yrSccaOGoY23i1gaaHBwcNH8fmCpbhzNx9D3+wFALh85R8sXLYa/42aj0qVzB8aK1Fdd1e8994wLFq8EnPmRqKVtxcWLZyJgsJCrF272dThERnNZEk0JCQEb775JpYvXw7VfdfpAEAIgdGjRyMkJAQJCY8vDUZERGDGjBl6bZ9MHIfwSeNlj/l50t63tfRzQw93NPNsiM79AhG75wDq1qkNAHizVzf0CegMAGjcwAOHEpPww46fETpmBIQQmLUgCtWq2mFN1HxYaDT4fnssxk6ajg2rIlGj+r3y7egR/z9baNzAA3fv5mP1ui0Y+mYvFBcXY9L0uQgOGoo6rrVA9ChmZmZITPwLn3w6BwCQlHQKTZo0xHvvDGMSNRHB1bmyMFkSPX78OKKjo0slUABQqVQIDQ3Fyy+//MRxpk6dirCwML02s1v/yBZnRWFbxQZutV9C6tVr8Pm/1bX13F31+tR1c0Va+r2S7x+JSdh38DAOxm6CjbU1AMCz4VgkHDmGH3f9onct9X7NmjTC8uj1KCgoQL62AKfOnsPZcymYvTAKAKDTCQgh0OLVAKxYOAs+3l7ldMZUkVy/noHTZ/7Wazt79jz69ulmoohI6WVYuZgsiTo7O+Pw4cNo1KjRQ7cfPnwYTk5OTxxHo9GUKt0WFmTJEmNFcufOXVz55zp6dHkdL9V0gmP1arh0+apen8tXruKVtvdmsPn590rgZir9y+JmKhV0j/kX6tlzKbCtYgO1Wo1KlSph69plets3/LADhxOP44tZH+Olms5ynBq9AA4mHEHDBvX02hrUr4vUVOX9g5deLCZLoh9++CHeffddJCYm4vXXX5cSZnp6OuLj47Fy5Ur85z//MVV4z735S1aiYzsfuDg7ISPrXyxd9S3Mzc3Qza8DVCoVRrzVD0u//hYN67ujUf16+HHnL7h4+Sq++PxjAECLpo1hW8UGH32+AKNHvAULjRpbforF1evpePV/2gAA9v52CFk3stGiaSNo1GocPHIUq/67EYGD+wG4V6KrX7eOXlwOVe2hVqtLtZOyLV68Egf2/4gpk0Owect2tG7thVGjhmD0+5NMHZpycXWuLEyWRIODg1G9enUsXLgQUVFRKC4uBnDvtg1vb29ER0djwICHlxQJSM/IwqRpc5GdmwsHezu83LwJvvtqIRyq2gMAhg3sA21BIeZGrkBu7i008KiLlYtmwbWWCwCgqr0dli/4DJEr1iBo3BQUFRXBw90NX84JR6P6dQEAlSpVwoYftmNe5AoICLi+5IKJIe+if88upjptqqD+TDyO/m+OwuefT8EnH0/AxUtXEPbBNKxfv9XUoSkXy7myUIkH71cwgcLCQmRl3SvBVq9eHZUrV3668bIuyBEW0RNZurQ3dQikEEUF8pa+82bKd0uadfh3T+70gnouHrZQuXJl1KxZ09RhEBEpB1fnyuK5SKJERPSMsZwrC74KjYiIyEiciRIRKRFX58qCSZSISIlYzpUFy7lERERG4kyUiEiB+OxceXAmSkREZCQmUSIiJXoO3ic6Z84cqFQqTJgwQWrLz89HcHAwqlWrBhsbG/Tr1w/p6el6+6WmpiIgIABWVlZwdHTExIkTUVRUpNdn7969aNmyJTQaDTw8PBAdHV3q+EuXLkWdOnVgYWEBHx8fHD582OBzYBIlIlIiEyfRI0eO4KuvvkLz5s312kNDQ7F9+3Zs3rwZ+/btw7Vr19C3b19pe3FxMQICAlBQUICDBw9izZo1iI6ORnh4uNTn4sWLCAgIQKdOnZCUlIQJEyZg1KhR2L17t9Rn48aNCAsLw7Rp03D06FG0aNEC/v7+yMjIMOg8novH/smNj/2jZ4WP/aNnRe7H/t2e2Ee2sWzmG/YM5Nu3b6Nly5aIiorC559/Di8vLyxatAg5OTmoUaMG1q1bh/79+wMAzp49i8aNGyMhIQFt27bFrl270L17d1y7dk16ccny5csxefJkZGZmQq1WY/LkyYiJicHJkyelYw4aNAjZ2dmIjY0FAPj4+KB169ZYsmQJAECn06F27doICQnBlClTynwunIkSESmR0Mn20Wq1yM3N1ftotdpHHjo4OBgBAQHw8/PTa09MTERhYaFee6NGjeDq6oqEhAQAQEJCApo1a6b3qkx/f3/k5ubi1KlTUp8Hx/b395fGKCgoQGJiol4fMzMz+Pn5SX3KikmUiEiJZCznRkREwM7OTu8TERHx0MNu2LABR48efej2tLQ0qNVq2Nvb67U7OTkhLS1N6vPgu6ZLvj+pT25uLu7evYusrCwUFxc/tE/JGGXFW1yIiOipTJ06FWFhYXptGo2mVL8rV65g/PjxiIuLg4WFxbMKr1wxiRIRKZCQ8YlFGo3moUnzQYmJicjIyEDLli2ltuLiYuzfvx9LlizB7t27UVBQgOzsbL3ZaHp6OpydnQEAzs7OpVbRlqzevb/Pgyt609PTYWtrC0tLS5ibm8Pc3PyhfUrGKCuWc4mIlMgEq3Nff/11nDhxAklJSdKnVatWGDJkiPRz5cqVER8fL+2TnJyM1NRU+Pr6AgB8fX1x4sQJvVW0cXFxsLW1haenp9Tn/jFK+pSMoVar4e3trddHp9MhPj5e6lNWnIkSEdEzUaVKFTRt2lSvzdraGtWqVZPag4KCEBYWBgcHB9ja2iIkJAS+vr5o27YtAKBz587w9PTEsGHDMG/ePKSlpeGTTz5BcHCwNBsePXo0lixZgkmTJmHkyJHYs2cPNm3ahJiYGOm4YWFhCAwMRKtWrdCmTRssWrQIeXl5GDFihEHnxCRKRKREz+lj/xYuXAgzMzP069cPWq0W/v7+iIqKkrabm5tjx44dGDNmDHx9fWFtbY3AwEDMnDlT6uPu7o6YmBiEhoZi8eLFqFWrFlatWgV/f3+pz8CBA5GZmYnw8HCkpaXBy8sLsbGxpRYbPQnvEyV6CrxPlJ4Vue8TvfV+V9nGqhK1S7axKhpeEyUiIjISy7lERErE94nKgkmUiEiBXsAreSbBci4REZGROBMlIlIilnNlwSRKRKRETKKyYDmXiIjISJyJEhEpkJzPzlUyJlEiIiViEpUFy7lERERG4kyUiEiJns9H51Y4TKJERArEa6LyYDmXiIjISJyJEhEpEWeismASJSJSIl4TlQXLuUREREbiTJSISIG4sEgeTKJERErEcq4sWM4lIiIyEmeiREQKxHKuPJhEiYiUiOVcWbCcS0REZCTORImIFEhwJioLJlEiIiViEpUFy7lERERG4kyUiEiBWM6VB5MoEZESMYnKguVcIiIiI3EmSkSkQCznyoNJlIhIgZhE5cFyLhERkZE4EyUiUiDOROXBJEpEpERCZeoIXghlSqKRkZFlHnDcuHFGB0NERFSRlCmJLly4sEyDqVQqJlEiogqA5Vx5lCmJXrx4sbzjICKiZ0joWM6Vg9GrcwsKCpCcnIyioiI54yEiIqowDE6id+7cQVBQEKysrNCkSROkpqYCAEJCQjBnzhzZAyQiIvkJnXwfJTM4iU6dOhXHjx/H3r17YWFhIbX7+flh48aNsgZHRETlQwiVbB8lM/gWl23btmHjxo1o27YtVKr//+U1adIEKSkpsgZHRET0PDM4iWZmZsLR0bFUe15enl5SJSKi55fSy7ByMbic26pVK8TExEjfSxLnqlWr4OvrK19kRERUboROJdtHyQyeic6ePRtdu3bF6dOnUVRUhMWLF+P06dM4ePAg9u3bVx4xEhERPZcMnom+8sorSEpKQlFREZo1a4aff/4Zjo6OSEhIgLe3d3nESEREMhNCvo+SGfXs3Hr16mHlypVyx0JERM+I0suwcjEqiRYXF2Pr1q04c+YMAMDT0xO9evVCpUp8nj0RESmHwVnv1KlT6NmzJ9LS0tCwYUMAwNy5c1GjRg1s374dTZs2lT1IIiKSF2ei8jD4muioUaPQpEkTXL16FUePHsXRo0dx5coVNG/eHO+++255xEhERDLjNVF5GDwTTUpKwp9//omqVatKbVWrVsWsWbPQunVrWYMjIiJ6nhk8E23QoAHS09NLtWdkZMDDw0OWoIiIqHzxPlF5lGkmmpubK/0cERGBcePGYfr06Wjbti0A4NChQ5g5cybmzp1bPlESEZGslP7MW7mohHhyRdvMzEzvkX4lu5S03f+9uLi4POI0SGHWBVOHQAph6dLe1CGQQhQV/CPreClN/WUbq97J3bKNVdGUaSb666+/lnccRET0DPHZufIoUxLt0KFDecdBRETPkI7lXFkY/XSEO3fuIDU1FQUFBXrtzZs3f+qgiIiIKgKjXoU2YsQI7Nq166Hbn4drokRE9HhcWCQPg29xmTBhArKzs/HHH3/A0tISsbGxWLNmDerXr4+ffvqpPGIkIiKZ8RYXeRicRPfs2YMvvvgCrVq1gpmZGdzc3DB06FDMmzcPERER5REjERG9IJYtW4bmzZvD1tYWtra28PX11ats5ufnIzg4GNWqVYONjQ369etX6tkEqampCAgIgJWVFRwdHTFx4kQUFRXp9dm7dy9atmwJjUYDDw8PREdHl4pl6dKlqFOnDiwsLODj44PDhw8bfD4GJ9G8vDw4OjoCuPekoszMTABAs2bNcPToUYMDICKiZ89Uj/2rVasW5syZg8TERPz555947bXX0KtXL5w6dQoAEBoaiu3bt2Pz5s3Yt28frl27hr59+0r7FxcXIyAgAAUFBTh48CDWrFmD6OhohIeHS30uXryIgIAAdOrUCUlJSZgwYQJGjRqF3bv//1acjRs3IiwsDNOmTcPRo0fRokUL+Pv7IyMjw6DzKdN9ovdr3bo1Pv/8c/j7+6Nnz56wt7dHREQEIiMjsWXLFqSkpBgUQHngfaL0rPA+UXpW5L5P9HS9ANnG8kyJear9HRwcMH/+fPTv3x81atTAunXr0L9/fwDA2bNn0bhxYyQkJKBt27bYtWsXunfvjmvXrsHJyQkAsHz5ckyePBmZmZlQq9WYPHkyYmJicPLkSekYgwYNQnZ2NmJjYwEAPj4+aN26NZYsWQIA0Ol0qF27NkJCQjBlypQyx27wTHT8+PG4fv06AGDatGnYtWsXXF1dERkZidmzZxs6HBERVXBarRa5ubl6H61W+8T9iouLsWHDBuTl5cHX1xeJiYkoLCyEn5+f1KdRo0ZwdXVFQkICACAhIQHNmjWTEigA+Pv7Izc3V5rNJiQk6I1R0qdkjIKCAiQmJur1MTMzg5+fn9SnrAxenTt06FDpZ29vb1y+fBlnz56Fq6srqlevbuhwRERkAnLeJxoREYEZM2botU2bNg3Tp09/aP8TJ07A19cX+fn5sLGxwdatW+Hp6YmkpCSo1WrY29vr9XdyckJaWhoAIC0tTS+Blmwv2fa4Prm5ubh79y5u3ryJ4uLih/Y5e/asQef+1G/RtrKyQsuWLZ92GCIieobkvMVl6tSpCAsL02vTaDSP7N+wYUMkJSUhJycHW7ZsQWBgIPbt2ydbPM9SmZLog7+cx/niiy+MDoaIiCoejUbz2KT5ILVaLb31y9vbG0eOHMHixYsxcOBAFBQUIDs7W282mp6eDmdnZwCAs7NzqVW0Jat37+/z4Ire9PR02NrawtLSEubm5jA3N39on5IxyqpMSfTYsWNlGuz+h9QTEdHz63l6mbZOp4NWq4W3tzcqV66M+Ph49OvXDwCQnJyM1NRU+Pr6AgB8fX0xa9YsZGRkSHeKxMXFwdbWFp6enlKfnTt36h0jLi5OGkOtVsPb2xvx8fHo3bu3FEN8fDzGjh1rUOx8AD0RkQKZ6tm5U6dORdeuXeHq6opbt25h3bp12Lt3L3bv3g07OzsEBQUhLCwMDg4OsLW1RUhICHx9faVXb3bu3Bmenp4YNmwY5s2bh7S0NHzyyScIDg6WZsOjR4/GkiVLMGnSJIwcORJ79uzBpk2bEBPz/6uIw8LCEBgYiFatWqFNmzZYtGgR8vLyMGLECIPO56mviRIREZVVRkYG3n77bVy/fh12dnZo3rw5du/ejTfeeAMAsHDhQpiZmaFfv37QarXw9/dHVFSUtL+5uTl27NiBMWPGwNfXF9bW1ggMDMTMmTOlPu7u7oiJiUFoaCgWL16MWrVqYdWqVfD3///Xvw0cOBCZmZkIDw9HWloavLy8EBsbW2qx0ZMYfJ9oRcD7ROlZ4X2i9KzIfZ/oMddeso31cuqPso1V0XAmSkSkQC/e9Mk0DH7YAhEREd3DmSgRkQLxpdzyKFMSNeQVZz179jQ6GLnwOhUR0ePxfaLyKFMSLbmP5klUKhVfyk1ERIpRpiSq0+nKOw4iInqGWM6VB6+JEhEpEBfnysOoJJqXl4d9+/YhNTUVBQUFetvGjRsnS2BERETPO4OT6LFjx9CtWzfcuXMHeXl5cHBwQFZWFqysrODo6MgkSkRUAbCcKw+D7xMNDQ1Fjx49cPPmTVhaWuLQoUO4fPkyvL298Z///Kc8YiQiIpkJoZLto2QGJ9GkpCR88MEHMDMzg7m5ObRaLWrXro158+bho48+Ko8YiYiInksGJ9HKlSvDzOzebo6OjkhNTQUA2NnZ4cqVK/JGR0RE5UIn40fJDL4m+vLLL+PIkSOoX78+OnTogPDwcGRlZWHt2rVo2rRpecRIREQyE1B2GVYuBs9EZ8+ejZo1awIAZs2ahapVq2LMmDHIzMzEihUrZA+QiIjoefVCvgqtkvolU4dARCQruV+FttfpTdnG6pi+WbaxKho+bIGISIF0LOfKwuAk6u7uDpXq0b/8Cxf4QmwiIlIGg5PohAkT9L4XFhbi2LFjiI2NxcSJE+WKi4iIyhEXFsnD4CQ6fvz4h7YvXboUf/7551MHRERE5U/pt6bIxeDVuY/StWtXfP/993INR0RE9NyTbWHRli1b4ODgINdwRERUjljOlYdRD1u4f2GREAJpaWnIzMxEVFSUrMEREVH5YDlXHgYn0V69euklUTMzM9SoUQMdO3ZEo0aNZA2OiIjoeWZwEp0+fXo5hEFERM8SZ6LyMHhhkbm5OTIyMkq1//vvvzA3N5clKCIiKl8CKtk+SmZwEn3UUwK1Wi3UavVTB0RERFRRlLmcGxkZCQBQqVRYtWoVbGxspG3FxcXYv38/r4kSEVUQOmVPIGVT5iS6cOFCAPdmosuXL9cr3arVatSpUwfLly+XP0IiIpIdn50rjzIn0YsXLwIAOnXqhB9++AFVq1Ytt6CIiIgqAoNX5/7666/lEQcRET1DL9w7ME3E4IVF/fr1w9y5c0u1z5s3D2++Kd/76YiIqPzoZPwomcFJdP/+/ejWrVup9q5du2L//v2yBEVERFQRGFzOvX379kNvZalcuTJyc3NlCYqIiMqX7jHvhaayM3gm2qxZM2zcuLFU+4YNG+Dp6SlLUEREVL6EjB8lM3gm+umnn6Jv375ISUnBa6+9BgCIj4/H+vXrsXnzZtkDJCIiel4ZnER79OiBbdu2Yfbs2diyZQssLS3RvHlz/PLLL+jQoUN5xEhERDJT+oIguRj1PtGAgAAEBASUaj958iSaNm361EEREVH54hOL5GHwNdEH3bp1CytWrECbNm3QokULOWIiIiKqEIxOovv378fbb7+NmjVr4j//+Q9ee+01HDp0SM7YiIionOigku2jZAaVc9PS0hAdHY2vv/4aubm5GDBgALRaLbZt28aVuUREFYjSV9XKpcwz0R49eqBhw4b466+/sGjRIly7dg1ffvllecZGRET0XCvzTHTXrl0YN24cxowZg/r165dnTEREVM64sEgeZZ6J/vbbb7h16xa8vb3h4+ODJUuWICsrqzxjIyKicsJn58qjzEm0bdu2WLlyJa5fv4733nsPGzZsgIuLC3Q6HeLi4nDr1q3yjJOIiOi5Y/DqXGtra4wcORK//fYbTpw4gQ8++ABz5syBo6MjevbsWR4xEhGRzPjYP3k81X2iDRs2xLx583D16lWsX79erpiIiKic6VTyfZTsqR+2AADm5ubo3bs3fvrpJzmGIyIiqhCMeuwfERFVbEpfECQXJlEiIgViEpWHLOVcIiIiJeJMlIhIgYTCFwTJhUmUiEiBWM6VB8u5RERERuJMlIhIgTgTlQeTKBGRAin9SUNyYTmXiIjISEyiREQKZKrH/kVERKB169aoUqUKHB0d0bt3byQnJ+v1yc/PR3BwMKpVqwYbGxv069cP6enpen1SU1MREBAAKysrODo6YuLEiSgqKtLrs3fvXrRs2RIajQYeHh6Ijo4uFc/SpUtRp04dWFhYwMfHB4cPHzbofJhEiYgUyFSvQtu3bx+Cg4Nx6NAhxMXFobCwEJ07d0ZeXp7UJzQ0FNu3b8fmzZuxb98+XLt2DX379pW2FxcXIyAgAAUFBTh48CDWrFmD6OhohIeHS30uXryIgIAAdOrUCUlJSZgwYQJGjRqF3bt3S302btyIsLAwTJs2DUePHkWLFi3g7++PjIyMMp+PSgjxwpXGK6lfMnUIRESyKir4R9bxFroOlW2s0NRvjd43MzMTjo6O2LdvH1599VXk5OSgRo0aWLduHfr37w8AOHv2LBo3boyEhAS0bdsWu3btQvfu3XHt2jU4OTkBAJYvX47JkycjMzMTarUakydPRkxMDE6ePCkda9CgQcjOzkZsbCwAwMfHB61bt8aSJUsAADqdDrVr10ZISAimTJlSpvg5EyUiUiA5Z6JarRa5ubl6H61WW6Y4cnJyAAAODg4AgMTERBQWFsLPz0/q06hRI7i6uiIhIQEAkJCQgGbNmkkJFAD8/f2Rm5uLU6dOSX3uH6OkT8kYBQUFSExM1OtjZmYGPz8/qU9ZMIkSESmQnO8TjYiIgJ2dnd4nIiLiiTHodDpMmDAB7dq1Q9OmTQEAaWlpUKvVsLe31+vr5OSEtLQ0qc/9CbRke8m2x/XJzc3F3bt3kZWVheLi4of2KRmjLHiLCxERPZWpU6ciLCxMr02j0Txxv+DgYJw8eRK//fZbeYVW7phEiYgUSM6XaWs0mjIlzfuNHTsWO3bswP79+1GrVi2p3dnZGQUFBcjOztabjaanp8PZ2Vnq8+Aq2pLVu/f3eXBFb3p6OmxtbWFpaQlzc3OYm5s/tE/JGGXBci4RkQKZanWuEAJjx47F1q1bsWfPHri7u+tt9/b2RuXKlREfHy+1JScnIzU1Fb6+vgAAX19fnDhxQm8VbVxcHGxtbeHp6Sn1uX+Mkj4lY6jVanh7e+v10el0iI+Pl/qUBWeiRET0zAQHB2PdunX48ccfUaVKFen6o52dHSwtLWFnZ4egoCCEhYXBwcEBtra2CAkJga+vL9q2bQsA6Ny5Mzw9PTFs2DDMmzcPaWlp+OSTTxAcHCzNiEePHo0lS5Zg0qRJGDlyJPbs2YNNmzYhJiZGiiUsLAyBgYFo1aoV2rRpg0WLFiEvLw8jRowo8/kwiRIRKZCp7m1ctmwZAKBjx4567atXr8bw4cMBAAsXLoSZmRn69esHrVYLf39/REVFSX3Nzc2xY8cOjBkzBr6+vrC2tkZgYCBmzpwp9XF3d0dMTAxCQ0OxePFi1KpVC6tWrYK/v7/UZ+DAgcjMzER4eDjS0tLg5eWF2NjYUouNHof3iRIRVQBy3yc6y22IbGN9fPk72caqaHhNlIiIyEgs5xIRKRBfhSYPJlEiIgV64a7jmQjLuUREREbiTJSISIFYzpUHkygRkQLJ+cQiJWM5l4iIyEiciRIRKZCOS4tkwSRKRKRATKHyYDmXiIjISJyJEhEpEFfnyoNJlIhIgXhNVB4s5xIRERmJM1EiIgXiPFQeTKJERArEa6LyYDmXiIjISJyJEhEpEBcWyYNJlIhIgZhC5cFyLhERkZE4EyUiUiAuLJIHkygRkQIJFnRlwXIuERGRkTgTJSJSIJZz5cEkSkSkQLzFRR4s5xIRERmJM1EiIgXiPFQeTKJERArEcq48WM5VkMmTxiLhYAxu/puMa1eP4/stX6NBg3p6fUYFDUF83GbcyDqLooJ/YGdna6JoqSIzMzPDjOkTcS45AbdyziP5zO/4+KMJen169+6KXTHrkH79JIoK/kGLFk1MEyzRU2ASVZBX27fFsmVr0K59D3TpNhiVK1XGrph1sLKylPpYWVli9897MWfulyaMlCq6SROD8d67b2P8hE/QtHlHTP14Nj78YAzGBo+U+lhbW+H3g4cx9aNZJoxUuXQyfpSM5VwFCegxVO/7yFETkHbtBLxbNseB3/4AAER+uQoA0OFV32ceH704fNu2wk/bd2PnrngAwOXLVzFoYC+0bu0l9fnuu+8BAG5utUwRouLxYQvy4ExUwUpKtTduZps2EHrhJBz6E691egX169cFADRv7ol2/9MGsbt/NXFkRPKq8DNRrVYLrVar1yaEgEqlMlFEFYNKpcIX/5mB338/jFOnkk0dDr1g5s5bAltbG5w6sQ/FxcUwNzfHp+FzsX79VlOHRv9H6WVYuTzXM9ErV65g5MiRj+0TEREBOzs7vY/Q3XpGEVZcX0bORpMmDfHW0PdNHQq9gN58swcGD+qLoW8Ho7VPF4wImoCw0NEYNuxNU4dG/0fI+D8le66T6I0bN7BmzZrH9pk6dSpycnL0PiqzKs8owopp8aLPEdDND36d38Q//1w3dTj0Apob8SnmzV+CTZt+wsmTZ/Hdd99jceRKTJ401tShEcnKpOXcn3766bHbL1y48MQxNBoNNBqNXhtLuY+2eNHn6N2rC15/401cunTF1OHQC8rKyhI6nf4Mpbi4GGZmz/W/2xWF5Vx5mDSJ9u7dGyqVCkI8uhzAhCifLyNnY/Cg3ujbbyRu3boNJ6caAICcnFvIz88HADg51YCzsyPq1asDAGjWtBFu3c5Dauo/uMkFSFRGO2LiMHXKOFy58g9OnU6Gl1dTTBj/LqLXbJD6VK1qD1fXl+BS0wkApHuW09IykJ6eaZK4lUT3mL93qexU4nEZrJy99NJLiIqKQq9evR66PSkpCd7e3iguLjZo3Erql+QI74VTVPDPQ9tHBoXiv2s3AQDCPw1D+KcfPLYP0ZPY2FhjxvRJ6N2rCxwdq+HatXRs3PQjPvt8IQoLCwEAbw8bgG++Xlhq35mfLcDMz7541iE/9x71/19jDXPrK9tYay//INtYFY1Jk2jPnj3h5eWFmTNnPnT78ePH8fLLL0OnM6zwwCRKRC8auZPoUBmT6LcKTqImLedOnDgReXl5j9zu4eGBX3/lfWVERHLjs3PlYdIk2r59+8dut7a2RocOHZ5RNERERIap8A9bICIiwyn9/k65MIkSESkQb3GRB2/aIiIiMhJnokRECsSFRfLgTJSIiMhInIkSESkQFxbJg0mUiEiBuLBIHiznEhERGYkzUSIiBTLhE19fKEyiREQKxNW58mA5l4iIyEiciRIRKRAXFsmDSZSISIF4i4s8WM4lIiIyEmeiREQKxIVF8mASJSJSIN7iIg+Wc4mIiIzEJEpEpEA6GT+G2L9/P3r06AEXFxeoVCps27ZNb7sQAuHh4ahZsyYsLS3h5+eHc+fO6fW5ceMGhgwZAltbW9jb2yMoKAi3b9/W6/PXX3+hffv2sLCwQO3atTFv3rxSsWzevBmNGjWChYUFmjVrhp07dxp4NkyiRESKJGT8nyHy8vLQokULLF269KHb582bh8jISCxfvhx//PEHrK2t4e/vj/z8fKnPkCFDcOrUKcTFxWHHjh3Yv38/3n33XWl7bm4uOnfuDDc3NyQmJmL+/PmYPn06VqxYIfU5ePAgBg8ejKCgIBw7dgy9e/dG7969cfLkSYPORyVewMJ4JfVLpg6BiEhWRQX/yDpe59pdZBvr5yuxRu2nUqmwdetW9O7dG8C9WaiLiws++OADfPjhhwCAnJwcODk5ITo6GoMGDcKZM2fg6emJI0eOoFWrVgCA2NhYdOvWDVevXoWLiwuWLVuGjz/+GGlpaVCr1QCAKVOmYNu2bTh79iwAYODAgcjLy8OOHTukeNq2bQsvLy8sX768zOfAmSgRkQLpIGT7aLVa5Obm6n20Wq3BMV28eBFpaWnw8/OT2uzs7ODj44OEhAQAQEJCAuzt7aUECgB+fn4wMzPDH3/8IfV59dVXpQQKAP7+/khOTsbNmzelPvcfp6RPyXHKikmUiEiBhBCyfSIiImBnZ6f3iYiIMDimtLQ0AICTk5Neu5OTk7QtLS0Njo6OetsrVaoEBwcHvT4PG+P+YzyqT8n2suItLkRE9FSmTp2KsLAwvTaNRmOiaJ4tJlEiIgWS82ELGo1GlqTp7OwMAEhPT0fNmjWl9vT0dHh5eUl9MjIy9PYrKirCjRs3pP2dnZ2Rnp6u16fk+5P6lGwvK5ZziYgUyFSrcx/H3d0dzs7OiI+Pl9pyc3Pxxx9/wNfXFwDg6+uL7OxsJCYmSn327NkDnU4HHx8fqc/+/ftRWFgo9YmLi0PDhg1RtWpVqc/9xynpU3KcsmISJSKiZ+b27dtISkpCUlISgHuLiZKSkpCamgqVSoUJEybg888/x08//YQTJ07g7bffhouLi7SCt3HjxujSpQveeecdHD58GL///jvGjh2LQYMGwcXFBQDw1ltvQa1WIygoCKdOncLGjRuxePFivZLz+PHjERsbiwULFuDs2bOYPn06/vzzT4wdO9ag8+EtLkREFYDct7i8+tLrso21/5/4J3f6P3v37kWnTp1KtQcGBiI6OhpCCEybNg0rVqxAdnY2XnnlFURFRaFBgwZS3xs3bmDs2LHYvn07zMzM0K9fP0RGRsLGxkbq89dffyE4OBhHjhxB9erVERISgsmTJ+sdc/Pmzfjkk09w6dIl1K9fH/PmzUO3bt0MOncmUSKiCkDuJNpexiR6wIAk+qJhOZeIiMhIXJ1LRKRAfBWaPJhEiYgUiElUHiznEhERGYkzUSIiBXoB15SaBJMoEZECsZwrD5ZziYiIjMSZKBGRAsn5uD4lYxIlIlIgXhOVB8u5RERERuJMlIhIgbiwSB5MokRECsRyrjxYziUiIjISZ6JERArEcq48mESJiBSIt7jIg+VcIiIiI3EmSkSkQDouLJIFkygRkQKxnCsPlnOJiIiMxJkoEZECsZwrDyZRIiIFYjlXHiznEhERGYkzUSIiBWI5Vx5MokRECsRyrjxYziUiIjISZ6JERArEcq48mESJiBSI5Vx5sJxLRERkJM5EiYgUSAidqUN4ITCJEhEpEN8nKg+Wc4mIiIzEmSgRkQIJrs6VBZMoEZECsZwrD5ZziYiIjMSZKBGRArGcKw8mUSIiBeITi+TBci4REZGROBMlIlIgPvZPHkyiREQKxGui8mA5l4iIyEiciRIRKRDvE5UHkygRkQKxnCsPlnOJiIiMxJkoEZEC8T5ReTCJEhEpEMu58mA5l4iIyEiciRIRKRBX58qDSZSISIFYzpUHy7lERERG4kyUiEiBuDpXHkyiREQKxAfQy4PlXCIiIiNxJkpEpEAs58qDSZSISIG4OlceLOcSEREZiTNRIiIF4sIieTCJEhEpEMu58mA5l4iIyEiciRIRKRBnovJgEiUiUiCmUHmwnEtERGQkleCcngBotVpERERg6tSp0Gg0pg6HXmD8s0YvEiZRAgDk5ubCzs4OOTk5sLW1NXU49ALjnzV6kbCcS0REZCQmUSIiIiMxiRIRERmJSZQAABqNBtOmTeNCDyp3/LNGLxIuLCIiIjISZ6JERERGYhIlIiIyEpMoERGRkZhEiYiIjMQkSli6dCnq1KkDCwsL+Pj44PDhw6YOiV5A+/fvR48ePeDi4gKVSoVt27aZOiSip8YkqnAbN25EWFgYpk2bhqNHj6JFixbw9/dHRkaGqUOjF0xeXh5atGiBpUuXmjoUItnwFheF8/HxQevWrbFkyRIAgE6nQ+3atRESEoIpU6aYODp6UalUKmzduhW9e/c2dShET4UzUQUrKChAYmIi/Pz8pDYzMzP4+fkhISHBhJEREVUMTKIKlpWVheLiYjg5Oem1Ozk5IS0tzURRERFVHEyiRERERmISVbDq1avD3Nwc6enpeu3p6elwdnY2UVRERBUHk6iCqdVqeHt7Iz4+XmrT6XSIj4+Hr6+vCSMjIqoYKpk6ADKtsLAwBAYGolWrVmjTpg0WLVqEvLw8jBgxwtSh0Qvm9u3bOH/+vPT94sWLSEpKgoODA1xdXU0YGZHxeIsLYcmSJZg/fz7S0tLg5eWFyMhI+Pj4mDosesHs3bsXnTp1KtUeGBiI6OjoZx8QkQyYRImIiIzEa6JERERGYhIlIiIyEpMoERGRkZhEiYiIjMQkSkREZCQmUSIiIiMxiRIRERmJSZSIiMhITKL0whs+fLjey587duyICRMmPPM49u7dC5VKhezs7Ef2UalU2LZtW5nHnD59Ory8vJ4qrkuXLkGlUiEpKempxiFSIiZRMonhw4dDpVJBpVJBrVbDw8MDM2fORFFRUbkf+4cffsBnn31Wpr5lSXxEpFx8AD2ZTJcuXbB69WpotVrs3LkTwcHBqFy5MqZOnVqqb0FBAdRqtSzHdXBwkGUcIiLORMlkNBoNnJ2d4ebmhjFjxsDPzw8//fQTgP8vwc6aNQsuLi5o2LAhAODKlSsYMGAA7O3t4eDggF69euHSpUvSmMXFxQgLC4O9vT2qVauGSZMm4cHHQz9YztVqtZg8eTJq164NjUYDDw8PfP3117h06ZL0wPSqVatCpVJh+PDhAO69Mi4iIgLu7u6wtLREixYtsGXLFr3j7Ny5Ew0aNIClpSU6deqkF2dZTZ48GQ0aNICVlRXq1q2LTz/9FIWFhaX6ffXVV6hduzasrKwwYMAA5OTk6G1ftWoVGjduDAsLCzRq1AhRUVEGx0JEpTGJ0nPD0tISBQUF0vf4+HgkJycjLi4OO3bsQGFhIfz9/VGlShUcOHAAv//+O2xsbNClSxdpvwULFiA6OhrffPMNfvvtN9y4cQNbt2597HHffvttrF+/HpGRkThz5gy++uor2NjYoHbt2vj+++8BAMnJybh+/ToWL14MAIiIiMB///tfLF++HKdOnUJoaCiGDh2Kffv2AbiX7Pv27YsePXogKSkJo0aNwpQpUwz+nVSpUgXR0dE4ffo0Fi9ejJUrV2LhwoV6fc6fP49NmzZh+/btiI2NxbFjx/D+++9L27/77juEh4dj1qxZOHPmDGbPno1PP/0Ua9asMTgeInqAIDKBwMBA0atXLyGEEDqdTsTFxQmNRiM+/PBDabuTk5PQarXSPmvXrhUNGzYUOp1OatNqtcLS0lLs3r1bCCFEzZo1xbx586TthYWFolatWtKxhBCiQ4cOYvz48UIIIZKTkwUAERcX99A4f/31VwFA3Lx5U2rLz88XVlZW4uDBg3p9g4KCxODBg4UQQkydOlV4enrqbZ88eXKpsR4EQGzduvWR2+fPny+8vb2l79OmTRPm5ubi6tWrUtuuXbuEmZmZuH79uhBCiHr16ol169bpjfPZZ58JX19fIYQQFy9eFADEsWPHHnlcIno4XhMlk9mxYwdsbGxQWFgInU6Ht956C9OnT5e2N2vWTO866PHjx3H+/HlUqVJFb5z8/HykpKQgJycH169f13sXaqVKldCqVatSJd0SSUlJMDc3R4cOHcoc9/nz53Hnzh288cYbeu0FBQV4+eWXAQBnzpwp9U5WX1/fMh+jxMaNGxEZGYmUlBTcvn0bRUVFsLW11evj6uqKl156Se84Op0OycnJqFKlClJSUhAUFIR33nlH6lNUVAQ7OzuD4yEifUyiZDKdOnXCsmXLoFar4eLigkqV9P84Wltb632/ffs2vL298d1335Uaq0aNGkbFYGlpafA+t2/fBgDExMToJS/g3nVeuSQkJGDIkCGYMWMG/P39YWdnhw0bNmDBggUGx7py5cpSSd3c3Fy2WImUikmUTMba2hoeHh5l7t+yZUts3LgRjo6OpWZjJWrWrIk//vgDr776KoB7M67ExES0bNnyof2bNWsGnU6Hffv2wc/Pr9T2kplwcXGx1Obp6QmNRoPU1NRHzmAbN24sLZIqcejQoSef5H0OHjwINzc3fPzxx1Lb5cuXS/VLTU3FtWvX4OLiIh3HzMwMDRs2hJOTE1xcXHDhwgUMGTLEoOMT0ZNxYRFVGEOGDEH16tXRq1cvHDhwABcvXsTevXsxbtw4XL16FQAwfvx4zJkzB9u2bcPZs2fx/vvvP/Yezzp16iAwMBAjR47Etm3bpDE3bdoEAHBzc4NKpcKOHTuQmZmJ27dvo0qVKvjwww8RGhqKNWvWICUlBUePHsWXX34pLdYZPXo0zp07h4kTJyI5ORnr1q1DdHS0Qedbv359pKamYsOGDUhJSUFkZORDF0lZWFggMDAQx48fx4EDBzBu3DgMGDAAzs7OAIAZM2YgIiICkZGR+Pvvv3HixAmsXr0aX3zxhUHxEFFpTKJUYVhZWWH//v1wdXVF37590bhxYwQFBSE/P1+amX7wwQcYNmwYAgMD4evriypVqqBPnz6PHXfZsmXo378/3n//fTRq1AjvvPMO8vLyAAAvvfQSZsyYgSlTpsDJyQljx44FAHz22Wf49NNPERERgcaNG6NLly6IiYmBu7s7gHvXKb///nts27YNLVq0wPLlyzF79myDzrdnz54IDQ3F2LFj4eXlhYMHD+LTTz8t1c/DwwN9+/ZFt27d0LlzZzRv3lzvFpZRo0Zh1apVWL16NZo1a4YOHTogOjpaipWIjKcSj1pxQURERI/FmSgREZGRmESJiIiMxCRKRERkJCZRIiIiIzGJEhERGYlJlIiIyEhMokREREZiEiUiIjISkygREZGRmESJiIiMxCRKRERkpP8FMtPsRzbukUYAAAAASUVORK5CYII=",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"baseline_results = model.evaluate(test_features, test_labels,\n",
" batch_size=BATCH_SIZE, verbose=0)\n",
"for name, value in zip(model.metrics_names, baseline_results):\n",
" print(name, ': ', value)\n",
"print()\n",
"\n",
"plot_cm(test_labels, test_predictions_baseline)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PyZtSr1v6L4t"
},
"source": [
"If the model had predicted everything perfectly (impossible with true randomness), this would be a [diagonal matrix](https://en.wikipedia.org/wiki/Diagonal_matrix) where values off the main diagonal, indicating incorrect predictions, would be zero. In this case, the matrix shows that you have relatively few false positives, meaning that there were relatively few legitimate transactions that were incorrectly flagged."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "P-QpQsip_F2Q"
},
"source": [
"### Changing the threshold\n",
"\n",
"The default threshold of $t=50\\%$ corresponds to equal costs of false negatives and false positives.\n",
"In the case of fraud detection, however, you would likely associate higher costs to false negatives than to false positives.\n",
"This trade off may be preferable because false negatives would allow fraudulent transactions to go through, whereas false positives may cause an email to be sent to a customer to ask them to verify their card activity.\n",
"\n",
"By decreasing the threshold, we attribute higher cost to false negatives, thereby increasing missed transactions at the price of more false positives.\n",
"We test thresholds at 10% and at 1%."
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.086420Z",
"iopub.status.busy": "2024-08-20T01:25:11.086140Z",
"iopub.status.idle": "2024-08-20T01:25:11.388083Z",
"shell.execute_reply": "2024-08-20T01:25:11.387435Z"
},
"id": "52bd793e04bb"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Legitimate Transactions Detected (True Negatives): 56848\n",
"Legitimate Transactions Incorrectly Detected (False Positives): 12\n",
"Fraudulent Transactions Missed (False Negatives): 17\n",
"Fraudulent Transactions Detected (True Positives): 85\n",
"Total Fraudulent Transactions: 102\n",
"Legitimate Transactions Detected (True Negatives): 56789\n",
"Legitimate Transactions Incorrectly Detected (False Positives): 71\n",
"Fraudulent Transactions Missed (False Negatives): 13\n",
"Fraudulent Transactions Detected (True Positives): 89\n",
"Total Fraudulent Transactions: 102\n"
]
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_cm(test_labels, test_predictions_baseline, threshold=0.1)\n",
"plot_cm(test_labels, test_predictions_baseline, threshold=0.01)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kF8k-g9goRni"
},
"source": [
"### Plot the ROC\n",
"\n",
"Now plot the [ROC](https://developers.google.com/machine-learning/glossary#ROC). This plot is useful because it shows, at a glance, the range of performance the model can reach by tuning the output threshold over its full range (0 to 1). So each point corresponds to a single value of the threshold."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.391511Z",
"iopub.status.busy": "2024-08-20T01:25:11.391271Z",
"iopub.status.idle": "2024-08-20T01:25:11.395745Z",
"shell.execute_reply": "2024-08-20T01:25:11.395138Z"
},
"id": "lhaxsLSvANF9"
},
"outputs": [],
"source": [
"def plot_roc(name, labels, predictions, **kwargs):\n",
" fp, tp, _ = sklearn.metrics.roc_curve(labels, predictions)\n",
"\n",
" plt.plot(100*fp, 100*tp, label=name, linewidth=2, **kwargs)\n",
" plt.xlabel('False positives [%]')\n",
" plt.ylabel('True positives [%]')\n",
" plt.xlim([-0.5,20])\n",
" plt.ylim([80,100.5])\n",
" plt.grid(True)\n",
" ax = plt.gca()\n",
" ax.set_aspect('equal')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.398811Z",
"iopub.status.busy": "2024-08-20T01:25:11.398558Z",
"iopub.status.idle": "2024-08-20T01:25:11.648306Z",
"shell.execute_reply": "2024-08-20T01:25:11.647646Z"
},
"id": "DfHHspttKJE0"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_roc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
"plot_roc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
"plt.legend(loc='lower right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Y5twGRLfNwmO"
},
"source": [
"### Plot the PRC\n",
"\n",
"Now plot the [AUPRC](https://developers.google.com/machine-learning/glossary?hl=en#PR_AUC). Area under the interpolated precision-recall curve, obtained by plotting (recall, precision) points for different values of the classification threshold. Depending on how it's calculated, PR AUC may be equivalent to the average precision of the model.\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.652276Z",
"iopub.status.busy": "2024-08-20T01:25:11.652020Z",
"iopub.status.idle": "2024-08-20T01:25:11.656619Z",
"shell.execute_reply": "2024-08-20T01:25:11.655923Z"
},
"id": "XV6JSlFGEqGI"
},
"outputs": [],
"source": [
"def plot_prc(name, labels, predictions, **kwargs):\n",
" precision, recall, _ = sklearn.metrics.precision_recall_curve(labels, predictions)\n",
"\n",
" plt.plot(precision, recall, label=name, linewidth=2, **kwargs)\n",
" plt.xlabel('Precision')\n",
" plt.ylabel('Recall')\n",
" plt.grid(True)\n",
" ax = plt.gca()\n",
" ax.set_aspect('equal')"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.659659Z",
"iopub.status.busy": "2024-08-20T01:25:11.659418Z",
"iopub.status.idle": "2024-08-20T01:25:11.912080Z",
"shell.execute_reply": "2024-08-20T01:25:11.911397Z"
},
"id": "FdQs_PcqEsiL"
},
"outputs": [
{
"data": {
"image/png": 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W7dA5y9+RJJkkNbZi+PFLn7Z7rQUz8vX6p0faPS41zqrVi84I2Lfk1c/0n88KWjmjyddH5ehn3xwVsG/2w/9TWW37I1tLv3GK5o7O9X3+8kiFrnpiQ7vnSdKqH84MCIdPrtujR9fu8n2Oj7Xox3NG6LwxuS2dDgAAgDAiHMFnzik5mnNKTsC+0mqHiivbX8i1xhHY3c7j9XbovJbsKqru0LnuFrrfVda5OnRuRQsh6Gi1Q6XVjnbPrTuhk5/b0/Gf1eMNrLnG4W527hPr9hCOAAAADEA4QpuykmwqS41r97jkE6bhmU0m9Tt+nsfrVY3DLa+35VbeF07oryPltXrz80JJ0js7iwO+N0nKSIxttihtary12bXS4mN9921LS1P7clPsirO2v/BtfGzgMVaLuUP3lBr+XPwl22PULzVODrfHF5L6JNo6dC0AAACEFuEIbXpyweROnZeWEKt1t3+tw8e/uPGALxydyCtp9sk5Wnbh6Havs2TeyVoyr3MLzq645fROnTc8Jymon9XfldPydeW0fL3xWYFu+PsmSdJJOUmduhYAAAC6hnCEbuG8MbnavP+Y9pRU+/Ydq3Zqe2HD+07PbtivY9UO3Xn+SPVPizeqzLDZWdj0XtdJ2YkGVgIAABC9CEfoFuJjY7TswjEB+17/9LAWPvOx7/MbnxcoN9Wuu+edEunywm67Xzgans3IEQAAgBEIR+i2Jg9K1+A+Cdpd3DSa9OS6vUqPb70VeF56vL45rm+zxW67u52FVZIkq8Wk/MwESQ2NHxpf03I63XK4pVqHWy5v4PJkMRaTrJamfR6PV/UuT4fua4sxy2xu+rNyuj1yuVt+N8yfySTZT3g/y7/etljMJsXGBP4MtX4NPVq6NgAAQCQQjtBtZSXZtWbRGXpp8yHd9uInvv0Prd7R5nlms0nfGNs33OWF1MT8NNmtZplMTUHn7If+p0NltX5HxehHG9Y0O/e+C0bp8ikDfZ/3HK3W2Q/9r0P3fffHZykvvWma4t8/2Kel//6i3fMGZybo7dvODNh349836b/bi1s+wc810/N1zzcCR/9G3fNmQPfBaYMz9NfvTm4WogAAAMKJcIRuzWQyaUROkixmU4utu1tSVtN+O+7u5v4L2m82EU3W7z6qwoq6gOAGAAAQboQjdHuj+qXorUVnaE9JVavHvLT5kFYcXzi2rKb9hVx7gokD0zQwoyEceL1elZSUKDMzs9mUwezjC/Y2irNaNH1IRofuYbMGjszkptg7dG5Oir3ZvpG5yR2azjfo+LRBf9MGZ8jj9Wr97qPyehvapee2cA8AAIBwIhyhRxiUmdDiL9WNfvPWTt92gq13PNa/vWy8b9vpdGrlypWaO3eSrNbm6zv565sap2eun9qpe547KlfnjurcArQ/PndEp86TpL9fN0WHy2o1/RdvS5LG5aUqxsKUOgAAEFm947dIRL3Jg9L1ycFySdK9r3+h5W+1/V5SezISYvXrS8dp/IC0UJSHDti8/5hve+JA/twBAEDkEY7QK7hOeB+pss7VpetV1rn0r48PEY4iaNO+pnA0gXAEAAAMQDhCr3DF1IH6/HCFjlbVd+k6FXUuFVc2XOPp9ftU0oXrnZybrJvOHBrQKhut2+wfjvIawtGu4io53e2/x5SVZFd6QlOLd4fLo91tvKPmb1BmgmwxtA4HAACEI/QSQ/ok6oXvT+vydZ5ev1dLXv3c93nl1oJOX2vl1gKN7p+qM07q0+W6osG5o3KVlhCrqjqXUuIb3qu67q8btaekup0zpXvmnaxrZgzyfS6sqNO5y9/t0H3f/r8zNLhPYueKBgAAvQrhCPAzeVC6Em0xqqrv2rS8Ri9tOqhkewzT8zrgxjOH6MYzhxhdBgAAiGKEI8DPiJxkbbxzlo51Ya2kW5/fog92l0qSXvvksP796WH9e+FpGtUvJVRlRo3zRufqaHX7UxtPyk4K+Jxgi9Flk/M6dI8ke9vd/wAAQPQgHAEnsFstyk2J6/T5gzITfeFIkrxe6eMDZeqfFqfU+Ng2zsSJbpszvFPnpSfEatmFY9o9rqrepYRY3jcCAAANWEgECLEl55+sRy+foOF+oxl3vfKZxv1stZ5ct8fAynCihc9s1tRla3TLsx+HbColAADouQhHQIjFxVo0d3Su+qU1H316d2eJARWhJS63Rxv3HlNhRb3e33WUESQAAMC0OiBc7jhvpLKSbNpVXKWP9ja0qX57W5G+9uDaoK/l9XpVXW3R8h3vyWRqvTV4kj1Gi+eO1NTBGZ0tO2p8caTCN1qUm2LXqi8KA74/46Q+slsJTAAARBPCERAmQ/ok6hffGqN/f3LYF44kaXcHWlO3zCTV1bR71OPv7CYcdcCGPU3vhW09VK7v/21TwPfrF3+tS++eAQCAnodwBITZaUMzNTk/XdsLK7twFa+cDqessVZJzUeOnG6PahxuSQ0Lp9796mdduFf4ZKfY9d0Zg7rFiEyCjX/9AQCAQPx2AIRZWkKsXrihawvUOp1OrVy5UnPnzpHV2rz19HMb9uv2l7dKkvYerdHe9fu6dL9wirWYdd3pg40uQ5dMylOc1aIj5XUtfp9IeAIAIOrw//5AL3BK3xRZLSY53V6jS2nXF4crtPqLQqXFWzV+QJos5tbfoQoni9mk+eP7tfr9t/7wvuJjLZoxNFPfnzm4zXe9AABA70A4AnqB0f1T9MHis3WorNboUlr04KodemdHsSTp5Y8P6eWPD0mSfjRnuG4+a6iRpbXoWLVDm/Y1vCd2rMahG84YYnBFAAAgEghHQC+RkWhTRqLN6DJaNCC95cYGezrdnCK8Ptxz1Lc9jeYWAABEDcIRgLD7ybkjNDwnWRW1Tq37qkTv72oIH//cdFBXTRuoMf1TjS3wBOt3NYWjosp6Pf7Obt/na08bJLPfVMAPdh/V1oPl7V6zb2qczhuTG7Dvn5sO6li1o91zJw9K19i8VN/n6nqXnvlwf6vHuz1ufXnYpCPr9uriSQMCQvP2gkrfKF5b4mItumLqwIB9a74s1O7i9gPtsOxEnTk8K2Df0+v3qt7paffcs0ZkaWhWou9zUWWdXv34cLvnSdKV0wYGNPvYvP+YNvl1imxNZlKsLhjfP2Dfa58cVmEr76P5GzcgVafmp/s+O90ePbVub4fqPX9sbkBHxD0l1XrrhJbyLbGYTfruaYMC9r27s1jbjrTf9GVgRrzOOSUnYN/zGw/qo+PPi8XcerOUGUMzdXLfZN/nshqHXtx4sN17StKlk/OUbG96X/KzQ+UB/5y1JiXOqktOzQvY98ZnR3SgtFan9E3W9KGZHbo/AHQU4QhA2CXZrbry+C/aVfUuXziSpP9uK+524WjT/qZfqF/dclivbmn65XzBjHyZ/ToGvr2tSH/yC0+tmT4ko1k4+vO7u7WtoP1faBd/fUSzcHTfyi/bOcuiV/ft0BnDswPC0acHyzpwrtQnydYsHL2y5bD+/Un7QeVbE/o3C0cPrdqh8lpnu+dmJdsCwtGRsroO1StJF0/qHxCO1u0s0UOrd7R73pj+Kc3C0d/W7w1owd+ahWcNbRaOOlrv2LzUgHC0vaCiQ+fGWS3NwtHKrQV6dkPrgbnRnFOym4WjP/xvtw6VNTwvbbnvglEB4ehotaPDP+u5o3ICwtFHe0s7dO7gzIRm4eiR/+7S1kMN/0Hi9f93mkb1S+lQDQDQEYQjABF1zfR8/WHtLt/nlz8+qHVflXTpmiaTNPvk7JB1weuXGqfPDlWE5FoAQqsxGEnyLWEAAKFCOAIQUdnJdp1zcrZWHZ8+tO9ojfYdbX9x2/Z8uKdU3xzXT32Suv7e1fJLx+uD3UdV62z+i5f5hK51F4zvp3F+ozqtSU+IbbbvjvNGqrLO1e65w3OSAj4nx1n16OUTWj3e5XLp448/1vjx49U3NfB9r6mDM9o8t5Etxtxs33dn5Ovro3JaODpQv9Tm75g9cNEYuTztd1Mce8Kf5cCM+A7VK0nxsYH/l/b10Tka4jcK1ZqUuObt8RfNHq5jNe1PeRzSJ/D6sRZzh+sd0ich4PO4vLQOnXviMyhJ35k8QKcPa3+KWXZy838+7pk3Uu9/uFHjx49XTEzrvxaM6hs4QpOdbO/wz5qRGPj8nzk8S9nJ9nbPi48NnObn9TY9Q7YYs8bmMWoEILQIRwAi7rwxuVr3VYmqQ/xffZ9ev1exlua/1IfSI0Vfdeq8XZI+2lPauXOLqiRJo/ql6KwRWbJbLZo7OrfV451Op7z7vfr6qJxm62LlpccrLz2+U3WMH5Cm8Z06U82mcnVUanxsmz9rW4ZmJWloVlL7B7Zg2pDONeKIsZg7XW9Oir3T547un6LR/TsXFM48qY9qvmr5eWlLoi2m0/UOykzQoMyE9g88wf7Spv+QMik/TbYY4xeUBtC7EI4ARNw3x/XTvDF95fZ2bV2mo1UOTV22xvf5d293Lrj0JK8tnNHt3tECIsX/fcXpQ2jGACD0CEcADGE2mwIaG3RGSpxVfZJsKq6sD1FV3d8nB8vV3uw0l8ulfZUNx7Y1TSoU0uNjNSCjcyNRQLD8w1FnR/cAoC2EIwA9VlysRW/+cKY+OVgW8C5Cb+L1Sjf+Y7McroY22He98lkHz4zRw599GL7C/Px8/qhmne2AUPN6vVq/q6l5y5gTutQtf2tHh/5DydzRuZrh1wK8rMahB97c3uY5JpM0Y0imvt7JaYQAeg7CEYAeLT0hVmed0Da6t7HFmH3hqDv68gid/RB+h8pqVVLV1CQj5oT3C//9yWHt6sA6XIP7JAaEo2qHW/9oY92wRn//YL/W3f61FhuOAOg9CEcA0M399buTtfLTIx3q9iZJHo9He/fuVX5+vszm8DSoeO+rEn11vFHEi5sO6rXj6x+ZTSZ9fVSOll04WqYWuqoBnZWeEKu89DgdKK3tUGe+cLBaeKaB3o5wBADd3IQBaZowIK3DxzudTq1cuVtz544IqvtYML739EZfOHK4PAEjW899dEA/PndEi+3Lgc6Kj43RW4vO0FdFVUqIbf7ry2NXTFR9B0ZYc1ICW4j3SbTp9f93Wpvn1DrdqqxzKiup/fbjAHo2whEAIGjfmzlYxVX1qqh1SpJcHm/AelV3/GurjBw4ykmO062zhynJHp5wCGPYYiw6pW/LLcuHZXeubXtsjFmj+rFeEoAGhCMAQNAm5afrXzfN8H3ecqBM8x9Z5/v8n88KjCgrQJ8km248c4jRZQAAehDCEQCgywZlJGhAenzAIp1G++xQuZ7d0P6L9qFmNknTBmfS4hwAeiDCEQCgy1LirfrvbWeqqLLO0Dq++9RGX/e8FVuPaMXWI4bUkRpv1QeLz5bdajHk/ug6h8ujC/+wTp8frpDXqzabQPzqojHKTWnqYrfmy0I99f7edu+RmWjTry8dF7Dv16t3aPP+Y+2ee9bwLH33tEEB+6596iM53O2/d/WDs4dpUn667/OXRyp0/8ov2z1Pkv5w2diAzy9sPKB/H2/I0pbh2Um68/yTA/bd9cpn2nu0/Q6DF03sr2+O6+f7XFnn1E3/2BxwTP+0eN153kgl2PjVFl3DEwQACAmL2RTwC6IR+qXau0Vr8bIapw6U1igutv1wZDaZlJtip7tfN7O/tFqfHWp6lt7dWdLqsbUOd8DnI+V1bR7fqH9a839evjxS0aFz89Kbj0yu21WiOmf74ejyKYHrklXUOjt0T0nNFqHed7S6Q+fWt1DXlgNl2nqovN1zpwxKD/jscntbvOfJuUm6clp+u9cD2kI4AgD0Gg9fOk5rtxer7oRfViPhUFmtfrNmp+/z7F+/0+FzR/dL0Us3TldsTHharyN4/dPiNS4vVVsOlBldCjooroUuhkCweIoAAL1Gst2qb4zta8i9PzlQFhCOgrH1ULkq6pzKTLSFuCp0lt1q0Ss3z1B1vUvtrTAWf8L0yUsm5Wn++H6tHN2kpbHC3142vkNrmsWYm5+98c7Z7Z4nNSws7W/iwDR9tnROh86NNQWOAN1y9jDdeObQds+ztDAy+vz3pzYbiWrJietLpcZbffXe++8v9PzGA5KkQZkJ7V8MaAfhCACAEBjTP0V3zztZm/a1/76IJNU43Hp7W5Hv88WPrW/xl+VQSbLH6Pavj9S0IRlhvEvv05l3WGJjzJ0eBezKe2qJnXzfJsZiVqKlY/U6nc6Az7YYizr7mk98J0d6TCaT72c9WNbUBGYw4QghQDgCACAETCaTFswYpAUzBrV/sBret/APR3tK2n8xvav+9M4uwhF6lb0lDeEoNd6qNBaeRggQjgAAMMDI3CTNPjlbG/aUhvU+dU636l0NU6GO1TjbORroOeqcbh0qq5XElDqEDuEIAAAD2GIsevyqSWG/z92vfqa/rt8nSTQXQK9S63Drssl52l1crVP6pkiS3t1ZrDv+9Vmb5/VLjdOvLx2nnBR7JMpED0M4AgCgFzspJyng88FjNeqfxgK16PnSEmK17MIxAftqHe52F6PeX1qjf39yWNfPHBzO8tBD0TMUAIBebEifxIDPsx7+nw4ea/uXR6CnssaYlZEQ2+Jf/pLjGB9Ay3gyAADoxU7smlbn9KigvM7XNtzldMvpkeqdbrn9/pupLcbMwrTocc4anqVNd7Xc0rygvE6fHCzT/qM1mpSf3uIxAOEIAIBebMKAND1+1SRd//RG376LHlt/wlExuu3DNQF7hvRJ0PPfn8baS+g1clLsyknJMboMdHNMqwMAoJebMjj4/0q+q7han9DAAUCUYeQIAIBeLtlu1b3zR+k/W4/I4/UGfOf1enX06FFlZGTIZDJp075jcrobjnlo1Q798X+7I1qrPdaiG88YwnpMAAxBOAIAIApcOXWgrpw6sNl+p9OplStXau7cUxUTE6PBP13p++6LIxWRLNGnrMah1xaeZsi90TuV1zr1vx3F+mD3UT3z4f5m38dZLbrjvJG6ooV/RhBdCEcAAECSZDKZdNGE/vrn5oM6YYApokqrHfrdmp1dvk7/9Dh9c2w/mc00loh2R6vqdcuzH7f6fa3TrX9uOkg4AuEIAAA0eeDisVp24WhFOhs9uW6P7l+5TZJ08FitHlq9IyTXNZtM+ua4fiG5FnquQZkJ+sHZw/TuzuKAZ7vW4da2gkpJovkIJBGOAADACWIske/XNCgzsf2DOuHLI5UamFEWsG9YVqISbPwKFE1MJpNunX2Sbp19UsD+D3cf1aV/+kCSlJceZ0Rp6Gb4NwMAADDc7JOz9cYPT9fhstouX+vnK77U7uJqSdJj/9ulx/63K+D7jIRYrV50htJPWBgU0cdutWjOKdnaX1qrYVlJRpeDboBwBAAAuoUROckakZPc5ev8Ye0uXzhqydFqhwrK6whH0Ni8VP3xyklGl4FuhHAEAAB6lV9dNFYvbDygWoc7YP9f1++V1yslxFo0LDs80/jQM5VWO1RZ52z3OLvVouxke8C+Q2W1crk97Z6bGh+rlDir77PL7dEhv5HSE7+HMQhHAACgVxmUmaCfnDsiYN+2ggo99f5eSdKUwRmyGvBeFbqvR/77lf7y3p52jzt9WKb+du2UgH3XPLFBO4uq2j33zvNG6rrTB/s+F1fV64wH1vo+W8wmPXHNqTrjpD4dLxwhRzgCAAC93rqvjvq29x6t1k3/2NSl69ljLLp6er7G5qV2sTKggdvj1bqvSghHBiMcAQCAXu+zQ+W+7d3F1W2+k9RR2wsrteKW07t8HRhvdL8UzR/Xt93jTspp3rThayOzdErf9t+VG9IncCpnnNWi+eP66uCxWm3cd0ySmFbXDRCOAABArzdjaKZe++Sw3J7QreBUVuPUsxv2S5Jyku06c3gfmUwsONsTzR/fT/PHd249rMVfH9mp81LjY7X82+P19w/2+cJRZiJNQoxGOAIAAL3eRRP7a84p2aqqd3XpOiu3Fuje17+Q1PAi/uKXt/q++9W3xuiSU/O6dH1En5Kqet82C9Eaj3AEAACiQpLdqiR716YtndRGl7tdxVU6eKymQ9cxmUzKTbbLbGakKdodrXL4tjMIR4YjHAEAAHTQ6cP66IXvT9PekoZ3lv66fq8+P1whSfrjO7v1x3d2d/hap/RN1r9umqHYGDrnRbPAkSOm1RmNcAQAABCEyYPSNXlQuiRp1ReFvnAUrM8PV6isxqGsE9bNQXRhWl33QjgCAADopJ/OHaE+SbGqrOvYu0wer1crtxb4Pl/6pw8Uyol1mUk2/epbY5SfmRDCqyKcHvnOBBVW1Otodb3sVovR5UQ9whEAAEAnDe6TqGUXjunw8UWVdQHhaE9J11uK+9tdUq3nPjqg278+ov2D0S1kJdsZPexGCEcAAAARkplg07dPzdObnxcohF3FVet0y+HySJL6pcWF7sJAlCEcAQAARIjZbNIvvjVGv/hWx0ebOuLmZzZrxadHJEkTBqSG9NpANCEcAQAA9HAfH19E1GySDpTW6HBZnaSGxWlH908xsjS04Uh5rf6ztUCZSTad0jdZQ/q03ioekWF4OHrkkUf0wAMPqKCgQGPHjtXvfvc7TZ48udXjly9frj/84Q/av3+/MjMzddFFF2nZsmWy25mrCQAAok9RRZ0OlzeEIY9XuuHvmwO+f+Q7E3TemFwjSkM7thVU6mfHFxWeeVIfzT45u9kxyfYYnTsqR7YYmjVEgqHh6Pnnn9eiRYv02GOPacqUKVq+fLnmzJmj7du3Kysrq9nxzzzzjG6//XY98cQTmj59unbs2KFrrrlGJpNJDz/8sAE/AQAAgLEsZpNiLWY53J4Wv99ZVKk6Z/PfqzrD5XTL6ZHqnW651bH1mSxmk6wW1nJqif8CsO/sKNY7O4pbPO6GM4bQZCNCDA1HDz/8sK6//notWLBAkvTYY49pxYoVeuKJJ3T77bc3O/7999/XjBkz9J3vfEeSlJ+fr8suu0wffvhhROsGAADoLjISbXr++1P1/q6jvn0rtx7xrb+0/K2dWv7WzhDeMUa3fbimw0dbzCZ9b+Zg/eRcfrk/UX5GfLvHXDF1AIvDRpBh4cjhcGjTpk1avHixb5/ZbNasWbO0fv36Fs+ZPn26/v73v2vDhg2aPHmydu/erZUrV+rKK6+MVNkAAADdzvgBaRo/IM33eVtBZacXpw01t8erVz4+RDhqwaT8dP3rpunaXdx6S/dzTslWkt0awaqim2HhqKSkRG63W9nZgXMrs7OztW3bthbP+c53vqOSkhKddtpp8nq9crlcuuGGG/TTn/601fvU19ervr5p5eGKioZ/UTidTjmdzhD8JJ3TeG8ja0DPwfOCYPC8IBg8L73TjTPzVedwqaIutH9fvR6vSo+VKj0tXSZz28vX1jrd+vRgw+9dZTUOXfSHdZKkU/om6ydzTmKq3XGjchM1KrftRgw99Z/P7vTvl47WYHhDhmCsXbtW999/vx599FFNmTJFX331lX7wgx/o3nvv1V133dXiOcuWLdPSpUub7V+1apXi49sfygy31atXG10CehCeFwSD5wXB4Hnpfc5PDdOF+0pSSbuH7auSPj3Y8KtmrdOjjfvKJEkb95UprmyPRqaGcKEndGvd4d8vNTU1HTrO5PV6DXkyHQ6H4uPj9c9//lPz58/37b/66qtVVlamV199tdk5p59+uqZOnaoHHnjAt+/vf/+7vve976mqqkpmc/P/AtHSyFFeXp5KSkqUnJwc2h8qCE6nU6tXr9bs2bNltTJUirbxvCAYPC8IBs8LghHM81LjcOmapzbp4wPlzb771oS+yktr/T9SJ9ljNH9srpLjoveZrKp3yWIyKS6253ap607/fqmoqFBmZqbKy8vbzACGjRzFxsZq4sSJWrNmjS8ceTwerVmzRgsXLmzxnJqammYByGJpeGBay3g2m002m63ZfqvVavjfpO5UB3oGnhcEg+cFweB5QTA68rykWK36182nyXm8i95Ff3hfnxxsCEovbT7c7j12FFbrlxeFdrHcnuTRVTv1+Lt7FB9r0d+vm6IJfu+U9TTd4d8vHb2/odPqFi1apKuvvlqTJk3S5MmTtXz5clVXV/u611111VXq16+fli1bJkmaN2+eHn74YY0fP943re6uu+7SvHnzfCEJAAAA3Ufju0VDs5J84agj9h6t1pYDZQH7+qfFKTOx+X/07o2OVje0+a5xuJVk61FvwvRohv5JX3rppSouLtaSJUtUUFCgcePG6Y033vA1adi/f3/ASNGdd94pk8mkO++8U4cOHVKfPn00b9483XfffUb9CAAAAOiAZReO1kUT+6vW6Wr1mA92l+pP7+yWJH24p1TzH1kX8H2sxax/3Txdp/RNCWut3UFpddMaSBlREgi7A8Nj6MKFC1udRrd27dqAzzExMbr77rt19913R6AyAAAAhEpsjFnThmS0eYzT3far8A63R18eqYyKcNS4QKzZJKVG8btXkWZ4OAIAAAAk6ZyTs3Xv/FHaVVQVsP+dncW+tYDueuUzLf3352GrIdlu1c/nj9JZI7LCdo+OaBw5SouPlbmdtukIHcIRAAAAugWTyaQrpw5stv/Gv2/yhaNap1sK47I5lXUuPffRfsPD0dHqhm7L6QmxhtYRbQhHAAAA6NauO32wCirqVFEbvlRU63DrcHmdJGnrwXItfnmrfnD2MOWk2MN2z9bUOFyqczZ0+SMcRRbhCAAAAN3axIFp+tdNM8J6j1WfF+h7f9skSTpcXqdnN+yXySTdf8HosN63JY3vG0mKmu583QXhCAAAAFFvTP9UZSbaVFJV79u3o6BSz27YL6mhU96Zw/tEpHOcf6c6Ro4ii3AEAACAqJeTYtf6xV/TPz7Yp3v+/YUkaeO+Y9q475jvmMn56Xrhhmlhr6XxfSOJcBRphCMAAABADQvWjurXepvwvUerVVRRp6zk8L6HNGVQhl7/f6fpaLVD/dPiwnovBCIcAQAAAMdNyk/XSzdO066ihu541Q6Xlh4fSSqqrNfk+9foWxP666FLxoathgRbTJshDeFDOAIAAAD8TByYrokD0yVJFXVO/ez1L+T1W5927fYigypDuJmNLgAAAADorpLtVv3usvE6f0yub1+fJDrI9VaMHAEAAABtOH9MX00amK7XPz0iSeqfFh/W+63+olA1DpcyEmyaNiRDFrMprPdDE8IRAAAA0I6Dx2p82+FukvD7t3fqk4PlMpmkr+6bG9Z7IRDT6gAAAIB2HDxW69sOdzg6enydo7T4WEaNIoyRIwAAAKAd/iNHxZX1Wv1FYbNjRvdLUU5K19t8Ny4CyxpHkUc4AgAAANrhP3L0x3d264/v7G52TLI9Ru/8+Cylxnc+1NQ63KpxuCURjozAtDoAAACgHWkdCCoVdS4VVNR16T5Hq+t92xmEo4hj5AgAAABoxy1fG6b+aXEqq3E2++6ZD/frUFnDyFJuctfeR2qcUidJGYmEo0gjHAEAAADtiIu16PIpA1v87qVNByVJCbEWJcd17dfro37hKD2B9ZQijWl1AAAAQCd5vV7fqJHT7dW3//SBnl6/t9PXK63yGzliWl3EEY4AAACATqp1ulXv8kiSHG6PPtxTqiWvfq6KuubT7zqiuKrpnaPMREaOIo1wBAAAAHRSfGyM5o3tK9MJyxHFWjr3a3aM2aS+KXZZLSb1SSIcRRrvHAEAAABd8LvLxuvXl4zVab/8rwoq6pSRECu71dKpa113+mBdd/pgeb1eeb0hLhTtYuQIAAAACIGiyoY23slxVm09WK56l7vT1zKZTDKbTe0fiJAiHAEAAABdVFhZL8/xkZ49JdWa9/v3dMlj640tCkEjHAEAAABdFGsx68SBnk8Olsvl9hhTEDqFd44AAACALuqTZNNfrjlV7+wo1jMf7le9y6OMhFjFBNGYweX26Iq/fKjMRJvG5aXqutMHh7FitISRIwAAACAEzhqepTvmjpTz+GhRbqo9qPNLqx36YHepXv/0iD7YfTQcJaIdhCMAAAAgRIr83j3KTYkL6lzWODIe4QgAAAAIkSPldb7tvinBjRwVVzaFI9Y4MgbhCAAAAAiRI+W1vu3D5XV67ZPDqnG4OnRuSZXDt83IkTEIRwAAAECIFPiNHK3+olC3PPux7n718w6dW8K0OsMRjgAAAIAQ6Z/W/D2jQ2W1LRzZnP+0uszE2JDVhI4jHAEAAAAhcu6oXP3juin6wdnDfPtyOvjukf/IEe8cGYN1jgAAAIAQmjE009fOW5L6drBrXcC0OsKRIRg5AgAAAELMv2tdR9c7apxWFxtjVpKNMQwj8KcOAAAAhNgRv/eMcjs4re7SUwdo39FquT1emUymcJWGNhCOAAAAgBDzHzl6adMhfXG4QtedPlh2q6XVc649bVAkSkMbCEcAAABAiBX5dZ5bsfWIVmw9IpPJpJvPGmpgVWgP7xwBAAAAIXZqflqzfXVOtwGVIBiEIwAAACDEbj5rqP5725m64Ywhvn25bXStq3W4VVnnlNfrjUR5aAXhCAAAAAgxk8mkQZkJslqaGiu01bVuxdYjGn3PKo246w39c9PBSJSIFhCOAAAAgDA5XObX0ruNrnWNbbzrXR7Fx7betAHhRTgCAAAAwqSgwr+ld+vT6gIWgE1kAVijEI4AAACAMDlyfOQoPtaiZHvrjaL9w1GfJMKRUQhHAAAAQBh4vV7feke5KfY2F3YtrvQfOYoNe21oGeEIAAAACIPyWqdqj7fv7pva+pQ6qWnkyBZjVqKNpUiNQjgCAAAAwsC/GUNOcuvNGKSmRWP7JNnaHGFCeBGOAAAAgDDwb8bglfTF4Qq5Pc3XMap3uVVW45QkZbcTohBehCMAAAAgDPxHjv656aDm/vZd3fLsx82OK6poet8oO5lmDEYiHAEAAABh0NJ6RZv3H2u2r8ivGUNWEiNHRuJtLwAAACAMvjmun8prndpVXKW/f7BfkpTVQpvuU/om680fzlRRZR1tvA1GOAIAAADCwGI2acGMQTp4rMYXjnJSmo8M2a0WDc9J0vCcpEiXiBMwrQ4AAAAIo4LypnePclPabukNYxGOAAAAgDA6HBCOeKeoO2NaHQAAABBGBeVNLb1zW1gM9vVPD8vh8igrya7pQzJkNrPOkVEIRwAAAEAY+bf07tvCyNHv3/5K2woqFWsxa/vPz41kaTgB0+oAAACAMDriN3LUUkOGxlbefZJsMpkYNTIS4QgAAAAIo8aGDCaTlJ0cGI4cLo9Kqx2SpCwWgDUc4QgAAAAIo8aGDFlJNlktgb9+F1f5LwBLODIa4QgAAAAIE4fLo5LjAai02qGvPbhWNz+zWTUOlySpqKLpfaQTR5UQeYQjAAAAIExqHC55vQ3bTrdXu0uqteLTI1q/66gkqbCCkaPuhHAEAAAAhElKnFWXTxmgtHirYv2m1MXFWiRJxZVNI0dZjBwZjnAEAAAAhInJZNJ9F4zWx0vO0ZxROb79fVMa1jti5Kh7YZ0jAAAAIAL8F4PdeqhcZbVOFVXyzlF3QjgCAAAAIuBIeVMQ+n/PfixJmnlSH+Wlx6moop6Ro26AcAQAAABEQEZCrA4eqw3YNyInSU9/d7K8x7s2/OSfn2rVFwXtXuub4/rpnm+cEpY6oxnhCAAAAIiAR6+YqP9sPaKP9pbqzc8LJTVNpTOZTJKkKodLx2qc7V6rut7l2/7icIW88iotPla5KXbftRA8whEAAAAQAf1S43Td6YPldHt94SjnhPeM+iTalJ8R3+61MhKbpuDd+cpWbd5fJknaed/XZbUQjjqLcAQAAABEkH9jhpyUwHDUMFUuuOlyjSNNSfYYWS00o+4K/vQAAACACPJvzJCb0vUOdcdqHJKk9ITYLl8r2hGOAAAAgAgqrGgIR2aT1KeLHercHq/KaxtGjlLjCUddRTgCAAAAIqhx5KhPkq3L0+DKa5063uhO6fHWrpYW9QhHAAAAQIQ43R4VV9VLkhJsMdpyoExHj3/ujNJqh287jWl1XUY4AgAAACKkqLLeN9Kzu7ha8x9Zp2m/eFvbCyo7db3G940kKY1pdV1GOAIAAAAixBZjlvmETtsOl0efHy7v1PWO+Y0c0ZCh6whHAAAAQIRkJtr0l2tO1YIZ+RqZm+zbn5XUua51/iNHqbxz1GWEIwAAACCCzhqepbvnnaLh2Ym+fbmpnQtHZcfXOJKkdKbVdRmLwAIAAAAG8F/vKCe5c+HoezMH68ppA1Va7aCVdwgQjgAAAAADFBxf7yjZHqMEW+d+LTeZTIqPjVF8LL/WhwLT6gAAAIAI83q9vpGj3JQ4g6tBI8IRAAAAEGGl1Q45XB5JUk5K56bUIfQYfwMAAAAizP99o76dbMYgSb95a6c8Xq9yU+z69uQBoSgtqhGOAAAAgAgrCGjG0PlpdU+9v0fHapwakB5POAoBptUBAAAAEXakoikc5XZyWp3b41VZbUMr7zTWOAoJwhEAAAAQYQXltb7tzr5zVF7rlNfbsJ2WQBvvUCAcAQAAABF2pKzrI0fHahy+bRaADQ3CEQAAABBhAQvAdjYcVTeFIxaADQ3CEQAAABBhjQvAJtlilGTv3PtCx2qcvu30BN45CgXCEQAAABBBDQvANrxz1JU1jhg5Cj3CEQAAABBB5bVO1Tm7vgBsqf87RzRkCAnCEQAAABBB/u8bdbYZgxTYkCGNkaOQYBFYAAAAIIKOBLTx7vwCsAPS4zVjaIaOVTvVJ8kWitKiHuEIAAAAiKBQjRxdPmWgLp8yMBQl4Tim1QEAAAARVOAXjv787m59+0/r9Y8P9xlYERoxcgQAAABEkP+7QruKq7WruFof7inVtyb0l91qMbAyMHIEAAAARNDc0blKtgeOUZhNJlkt/GpuNEaOAAAAgAiaPiRTW5acI7fXq6n3r9HRaoeykmyymE0dvobD5dHpv3pb6Qk2TRucoSXzTg5jxdGDcAQAAABEmNlsktPl0dHjC7kG25ihtNqhwop6FVbUKy+t8x3vEIixOwAAAMAAheX1vu3cIFt6l1Q1nZuRSBvvUCEcAQAAAAY47LfeUbAjR40jTpKUmcgCsKFCOAIAAAAM4N/SOyfYcOQ/cpRAOAoVwhEAAABgAP+Ro76pwU2rK/UbOWJaXegQjgAAAAAD+I8cPfX+Xi18ZrPe+OxIh84tqfIPR4wchQrd6gAAAAADHPULOBv2lEqS3visQJ//LEu2mLYXg/WfVpfJyFHIMHIEAAAAGOCsEVk6cWkjt9crs6n99Y78GzLwzlHoMHIEAAAAGOCiif11zinZqq536fzfvqej1Q71SbTJaml//KJx5MhsklLjCUehQjgCAAAADJJstyrOalFpzfHFYDvYmOGHs07SgWM1qqp3yXLi8BM6jXAEAAAAGKiosl5eb8N2bnLHWnqfNSIrjBVFL945AgAAAAx0pKyppXew6x0htAhHAAAAgIGO+LX0ziUcGYppdQAAAICBjvgtBtuRd47Ka5zaV1qtjESbMhNj2237jY4jHAEAAAAGCnbkaMPeUl3/9EZJ0v/NPkn/7+xhYast2jCtDgAAADBQgV84yulAQwb/BWAzWAA2pAhHAAAAgIEOHw9HJpOU3ZFw5L8AbCJrHIUS4QgAAAAwUMHxd44yE22KjWn/1/MSv5GjTMJRSBGOAAAAAIM43R4VVTaEnawkm+qcbrk93jbPOVrlN3KUwLS6UCIcAQAAAAbxXwD288MVGnHXGxp9z5t647MjrZ5ztNr/nSNGjkKJcAQAAAAYxOX2NNtX43Dr9U/bCEfHR45iY8xKtNF8OpQIRwAAAIBBBqTH6yfnjtC0wRkamZvs258W3/qIUMnxcJSZECuTyRT2GqMJ4QgAAAAwiMlk0o1nDtGz35uqW7421Lc/p5X1jjwer0qPT6ujjXfoEY4AAACAbqAji8GW1TrV2K+B941Cj0mKAAAAQDdQUOG3GGwr4Sg9IVbbf36uSqsd7Xa1Q/AIRwAAAEA34D9y1DclrtXjbDEW5bbxPTqPaXUAAABAN3CkrNa33drIEcKLcAQAAAB0A40jR2nxVtmtFoOriU5MqwMAAAAM5vF4VXj8naOyWqdG3/OmbDEW3XzWEC2YMch33H+2HtFnh8vVJ9Gm88f2VSYd60KKcAQAAAAYzOH2yHW8wYLXK1XWuVQpl55ctzcgHL31ZZFe2nxQktQvLV6DMhOaXSsvPU62GEaeOoNwBAAAABjMbrXox+cO1ysfH5LL7dXukmpJ0tGqet30j02KtZh1xdSBKqmq951z/dMbW7zW6ltnalh2UkTq7m0IRwAAAEA3cNOZQ3XTmUNVVuPQuJ+tliRVO9xaubVAkvTpwXIN7pNoZIm9nuENGR555BHl5+fLbrdrypQp2rBhQ5vHl5WV6eabb1Zubq5sNptOOukkrVy5MkLVAgAAAOGVEmfVqflpzfZ7JS05/2RdMz1fF03s3+pfSXZr5IvuJQwdOXr++ee1aNEiPfbYY5oyZYqWL1+uOXPmaPv27crKymp2vMPh0OzZs5WVlaV//vOf6tevn/bt26fU1NTIFw8AAACEgclk0gvfn6aiynpV1rk06+H/SZKykmwakBGve75xSrvXOHf5Ozpa7VD/tDj966YZ4S651zA0HD388MO6/vrrtWDBAknSY489phUrVuiJJ57Q7bff3uz4J554QqWlpXr//fdltTYk4vz8/EiWDAAAAISdyWRSdrJd1fVVvn3ZyR1f+6iosl6l1Q7ZrYZPFOtRDPvTcjgc2rRpk2bNmtVUjNmsWbNmaf369S2e89prr2natGm6+eablZ2drVGjRun++++X2+2OVNkAAABAxBRWNDVg6OjCsG6PV2U1DklSenxsWOrqrQwbOSopKZHb7VZ2dnbA/uzsbG3btq3Fc3bv3q23335bl19+uVauXKmvvvpKN910k5xOp+6+++4Wz6mvr1d9fdNDVVFRIUlyOp1yOp0h+mmC13hvI2tAz8HzgmDwvCAYPC8IBs9L5B0+Vu3bzkywdujP/liNQ8e7gislLsawv1/d6XnpaA09qludx+NRVlaW/vSnP8lisWjixIk6dOiQHnjggVbD0bJly7R06dJm+1etWqX4+Phwl9yu1atXG10CehCeFwSD5wXB4HlBMHheIuedwyZJDWsWHfrqC60s+7zdcwprpcZf82uOFRvevKw7PC81NTUdOs6wcJSZmSmLxaLCwsKA/YWFhcrJyWnxnNzcXFmtVlksTYtajRw5UgUFBXI4HIqNbT5suHjxYi1atMj3uaKiQnl5eTrnnHOUnJwcop8meE6nU6tXr9bs2bN9708BreF5QTB4XhAMnhcEg+cl8rb8Z7u0b58kac7MqS12sTvRpn3HpC0fSZJGDcvX3Lkjwlpja7rT89I4e6w9hoWj2NhYTZw4UWvWrNH8+fMlNYwMrVmzRgsXLmzxnBkzZuiZZ56Rx+OR2dzwutSOHTuUm5vbYjCSJJvNJpvN1my/1Wo1/G9Sd6oDPQPPC4LB84Jg8LwgGDwvkVNc5fBtP7fxkN78okin9E3RxZP6y2QytXhOpcPr285Mshv+96o7PC8dvb+h7SsWLVqkxx9/XH/961/15Zdf6sYbb1R1dbWve91VV12lxYsX+46/8cYbVVpaqh/84AfasWOHVqxYofvvv18333yzUT8CAAAAEDZH/cLRa58c1l/X79OPX/pUH+4pbfWcY9VN56Ql0JAhGIa+c3TppZequLhYS5YsUUFBgcaNG6c33njD16Rh//79vhEiScrLy9Obb76pW2+9VWPGjFG/fv30gx/8QD/5yU+M+hEAAACAsJmUn6b1u48221/rbL1bc2lNUziiW11wDG/IsHDhwlan0a1du7bZvmnTpumDDz4Ic1UAAACA8RbNPknzx/dTdb1Lv3lrp9ZsK5IkZSe13tbbf+QolXAUFMPDEQAAAICWmUwmDemTKElye5veJcpObv5OfaOLJ/XX2LxUlVY7NDQrMew19iaEIwAAAKAHKDq+IGyM2aS0NkaEhmYlaWhWUqTK6lUMbcgAAAAAoGOKKuskSVlJNpnNLXeqQ9cQjgAAAIBuzun2qOR457qs5NbfN0LXMK0OAAAA6OZKqup921lJrb9vJEnv7ChWkj1GfZJs6p8WH+7SehXCEQAAANDNFVY0haPsNkaO3B6vrn5yg7xeaWz/FL268LRIlNdrMK0OAAAA6OaKKup82211qiuvdaqxqR0LwAaPcAQAAAB0c4WVftPq2hg5OsYCsF1COAIAAAC6Of+Ro7beOfJfAJaRo+ARjgAAAIBurqiD7xyV+oWjdMJR0GjIAAAAAHRzhZVNI0cX/eF9mc0mDUiP15+umqR+qXG+7/yn1aXGWyNaY2/AyBEAAADQzdU53b7taodblXUufX64Qm99URhwXGm107fNO0fBY+QIAAAA6OZuOnOoahzbVV3vUlmNU0ePT597YeMBfbjnqOJjY3TDGYMDRo545yh4hCMAAACgm5t5Uh/NPKmPJOk3b+3Ur9/aIUn6/HCFPj9cIUkqrqwPaNbAO0fBY1odAAAA0IOcNixDtpjmv8Z7vF7V+E2/S2NaXdAYOQIAAAB6kIkD07VlyTkqq3VoT0m1vvP4h5KkPok2PXzpOP36Eo/KahzKYOQoaIwcAQAAAD1MXKxFuSlxMsnk25d5fEpdbIxZWcl2mc2m1k5HKwhHAAAAQA9VUtW0/lFmIiNFXUU4AgAAAHqo4sqmcNTHrxkDOod3jgAAAIAeyn/kKNZi1k/++akyEmM1cWCazh6ZbWBlPRPhCAAAAOih/MORR9LzGw9Ikr4zZQDhqBOYVgcAAAD0UCVVTYu+PvfhAd92sp0xkM4gHAEAAAA9VGl1Uzhat6vEt/3F8YVhERzCEQAAANBDTR6U3uJ+k4k23p3BeBsAAADQQy3++ghdMilPNQ6X7lvxpT7cUypJykm2G1xZz0Q4AgAAAHook8mkoVmJkiSn2+Pb3zeNcNQZTKsDAAAAeoFjNU7f9oC0eAMr6bkIRwAAAEAvUFHrF44yEgyspOdiWh0AAADQC9Q43L7trCSbb/v8372rbUcqWzxnxtBM/eXqSYqxMGYiMXIEAAAA9AouT9M7R5mJTeHI5fbK5Wn5r//tKNaWA2UGVNs9MXIEAAAA9ALp8bEqrKxXQqxFcbEW3/5h2UmynjAydKis1rdGktlM2+9GhCMAAACgF6g/3q0uw2/USJJ+d9n4Zscuen6LXv74kCQpJc4a/uJ6CKbVAQAAAD2c0+1R2fFudZmJse0ebzabFH98dIlw1ISRIwAAAKCHa5wiJzUfOWrJgxeP1YMXj5XD5ZHVwrS6RoQjAAAAoIcrrqz3bWd2IBw1io1hIpk/whEAAADQwx31Gzl6adNBvf7pYUnS1MEZeuQ7EwhBHcSfEgAAANDDOVxNbbwdbo8q61yqrHNp9ReF2lHY8hpHaI6RIwAAAKCHO21opuaN7asvDpdLkgrK61R9fFFYu9UScKzD5dGtL2xRst2qUf2SdfmUgRGvt7siHAEAAAA9XFysJaBl91VPbNA7O4olNe9eV17r1IpPj0iSZo3MIhz5YVodAAAA0MuUVjc0aLCYTUq2B7bqrqhz+raTaeMdgHAEAAAA9DJHqxoaNKTFx8psDmzVXV7rF47shCN/hCMAAACgF/F6vb7udS0tCOsfjlgANhDhCAAAAOhFqupdvu516QnNw1EF4ahVhCMAAACgFyn1W/Moo4UFYf3DEe8cBSIcAQAAAL2I/4KwGS2MHDGtrnWEIwAAAKAXaWzGILUyra7O5dsmHAVinSMAAACgF2ls4y1J7+0s0dGqhs+nDkrX+WP6qrzGf1odccBfh/80Pv300w5fdMyYMZ0qBgAAAEDXlPmFnw17S7Vhb6kk6a/r92lETpImDExVvcut8lqnMhKav5MUzTocjsaNGyeTySSv19vi943fmUwmud3ukBUIAAAAoOMmDEyTxWyS29P89/bqercuPXWALj11gAGVdX8dDkd79uwJZx0AAAAAQuDU/HStX/w1FZTXSZJ++cY2rfvqqKSW30FCkw6Ho4EDB4azDgAAAAAhkpVkV1aSvdn+NMJRmzocjl577bUOX/Qb3/hGp4oBAAAAEFql1Q3vIMVazEqItRhcTffW4XA0f/78Dh3HO0cAAABA93Hs+LpHaQlWeb3SyCX/UaLNqimD0/XIdyYYXF330uFw5PF4wlkHAAAAgBDzer0qrWkIR2U1Tl30h/dV5/SozlmvQ8dqDK6u+2ERWAAAAKCXcrq9crgaBjnqXR5tPlDm+25/aa1BVXVfnV71qbq6Wv/73/+0f/9+ORyOgO9uueWWLhcGAAAAoGtiY8y6aGJ/vbT5oE5ckafO6dbv1uyUJKXEW/XNsf2UEm81oMruo1Ph6OOPP9bcuXNVU1Oj6upqpaenq6SkRPHx8crKyiIcAQAAAN3EgxeP1S8uHC2vpP98dkS3PLtFklTjcOuh1Tt8x23ed0zLvz3emCK7iU5Nq7v11ls1b948HTt2THFxcfrggw+0b98+TZw4UQ8++GCoawQAAADQBTEWs6wWs9R8XVifvUd5B6lT4WjLli36v//7P5nNZlksFtXX1ysvL0+/+tWv9NOf/jTUNQIAAAAIgYo6l297wYx8/fayppGi5LjonlIndTIcWa1Wmc0Np2ZlZWn//v2SpJSUFB04cCB01QEAAAAImfJap2972uAMjc9L9X1Osne6HUGv0ak/gfHjx+ujjz7SsGHDdMYZZ2jJkiUqKSnR3/72N40aNSrUNQIAAAAIgcY1jyQpNT5WFXVNYSnZzshRp0aO7r//fuXm5kqS7rvvPqWlpenGG29UcXGx/vjHP4a0QAAAAAChUeY3cpQWb1VFbdM0u+Q4Ro469ScwadIk33ZWVpbeeOONkBUEAAAAIDyuPW2Qzh6RpWM1TuWmxmlPSbXvO0aOOhmO9uzZI5fLpWHDhgXs37lzp6xWq/Lz80NRGwAAAIAQGpmbrJG5yb7P/g0aaMjQyWl111xzjd5///1m+z/88ENdc801Xa0JAAAAQARU1Pq/c8S0uk6Fo48//lgzZsxotn/q1KnasmVLV2sCAAAAEAEBDRkYOerctDqTyaTKyspm+8vLy+V2u7tcFAAAAIDQ8nq9+u/2IqXGxyoryab+afGBDRl456hzI0czZ87UsmXLAoKQ2+3WsmXLdNppp4WsOAAAAAChUVnv0nef2qgLH31fi1/eKilw5CiFbnWdGzn65S9/qZkzZ2r48OE6/fTTJUnvvvuuKioq9Pbbb4e0QAAAAABdV1btH4QaRokC3zli5KhTI0cnn3yyPv30U11yySUqKipSZWWlrrrqKm3bto1FYAEAAIBuqKy2aQHY974q0Xm/fVfvfVXi2/fCxgPNzvnG79/Teb99Vwue3KAdhc1fq+ltOj121rdvX91///2hrAUAAABAmNQ5Pb7tshqnymqcAd8XV9Y3O+fzwxVye7z6XFJmok0PXDw23GUaqlMjR1LDNLorrrhC06dP16FDhyRJf/vb3/Tee++FrDgAAAAAoTGqX7KmDc5QrMXs+8ufxdw8GsSYTb7tGkfvb7zWqXD00ksvac6cOYqLi9PmzZtVX9+QMsvLyxlNAgAAALqh+NgYPfu9qdpx39d9fzWubTQoM0FL5p3c7Jx//7+mZmtxsZaI1WqUToWjn//853rsscf0+OOPy2ptenFrxowZ2rx5c8iKAwAAABAeHo9XlfUNrbxbWwDWf7QonnDUsu3bt2vmzJnN9qekpKisrKyrNQEAAAAIs2qHS15vw3ZrC8DW+oUjRo5akZOTo6+++qrZ/vfee0+DBw/uclEAAAAAwquirmkB2PhYi+qcbtU53XK4mho31Dr9jrH2/nWQOvUTXn/99frBD36gJ554QiaTSYcPH9b69ev1f//3f1qyZEmoawQAAAAQYv5rHL35eaFG3PWGpIYmDN+bOVg/PndE1E2r61Q4uv322+XxeHT22WerpqZGM2fOlM1m049+9CNdd911oa4RAAAAQIglxLYcBVwer55ct7dZOGJaXStMJpPuuOMOlZaW6rPPPtMHH3yg4uJipaSkaNCgQaGuEQAAAECIDciI113nn6xpgzM0dXC6pg5OV2xMQzyIsTS08D4pO0nfnzlYV04dqBE5SUaWGxFBjRzV19frnnvu0erVq30jRfPnz9eTTz6pCy64QBaLRbfeemu4agUAAAAQQteeNkjXntY0uHHqfW+puLJeSbaGmDAuL1Xj8lINqi7yggpHS5Ys0R//+EfNmjVL77//vi6++GItWLBAH3zwgR566CFdfPHFslh6/3AbAAAA0BtV1jW8h5Rkb7l7XW8XVDh68cUX9fTTT+sb3/iGPvvsM40ZM0Yul0uffPKJTCZT+xcAAAAA0C053R7VORs61SW1su5RbxfUO0cHDx7UxIkTJUmjRo2SzWbTrbfeSjACAAAAergqv9bejeGozumWy+1p7ZReJ6hI6Ha7FRsb23RyTIwSExNDXhQAAACAyKr0C0eJx6fV/fTlrXr540OKtZi16taZys9MMKq8iAgqHHm9Xl1zzTWy2WySpLq6Ot1www1KSAj8Q3r55ZdDVyEAAACAsKusb1r3qHHkqLGVt8Ptkd3a+3sLBBWOrr766oDPV1xxRUiLAQAAAGCMyham1dU4/dY5IhwFevLJJ8NVBwAAAAAD+Yej5OPT6modTftYBBYAAABAVGhs4y1JibbAaXUxZpNvgdjerPf/hAAAAADaVVXffFpd7fFwFA2jRhLhCAAAAIBOfOfo+LS64+8cxROOAAAAAESLijam1cXHRseisIQjAAAAAC0uAts4rS4a2nhLhCMAAAAAat6tzuX2yOH2SIqeaXXRMT4GAAAAoE3+3eqS7DEymUx68YZpqnG4CUcAAAAAoof/yFGiPUYWs0mn5qcbWFHkMa0OAAAAgK+Vt91qltUSnTEhOn9qAAAAAAEaR44a23hHI6bVAQAAAPC18k463sa7pKpeG/eWKi42RoMyEjQgI97I8iKCkSMAAAAgynm9Xt+0usY23p8frtANf9+sq5/YoBc3HTCyvIghHAEAAABRrtrhltfbsN04ra66vqlBQ4ItOiacEY4AAACAKHdiG2+pqUGDRDgCAAAAECWq/Nt4Hw9CNfX++6JjnSPCEQAAABDlKgJGjo5Pq3O4ffsSYhk5AgAAABAFymubwlFKXEM4qqpvPprU2xGOAAAAgCgXGI4aghANGQAAAABEnfIav3AU33zkiHAEAAAAICqU1zYFocZpddVMqwMAAAAQbVp658hsMik2piEuJERJt7roiIAAAAAAWuUfjpKPd6v7wxUTJUlOt0cxZpMhdUUa4QgAAACIci2NHDWyWqJnsln0/KQAAAAAWlThP3J0QjiKJoQjAAAAIMo1jhzZYsyyW6Pj/aKWMK0OAAAAiHKN4ahxSp3X69VtL36quFizhvZJ1DUzBhlZXsQQjgAAAIAoV1EXGI7qXR69tPmgJGnyoPSoCUdMqwMAAACimNPtUY3DLSm61ziSCEcAAABAVGupU111vdu3L4FwBAAAACAatBSOqgJGjqKnQQPhCAAAAIhi5S208a52NIWjhFhGjgAAAABEgfZGjphWBwAAACAqtLQALA0ZAAAAAESdlhsyROfIUfT8pAAAAACaKa9pCkf//uSwth4s0xdHKnz74mOjpyED4QgAAACIYv7vF/1vR7H+d8L3/iNLvR3T6gAAAIAodmp+epvfN061iwaMHAEAAABRbNbJ2Vq/+Gsqrqz37Xt2wwE9u2G/JCnJHj2RIXp+UgAAAAAtyk2JU25KnO/zvz857NtOskfPyBHT6gAAAAAEqKxreg8pmkaOCEcAAAAAAqzZVuTbtlujJzJEz08KAAAAoENqHE0jR2nxsQZWElndIhw98sgjys/Pl91u15QpU7Rhw4YOnffcc8/JZDJp/vz54S0QAAAAiCJOl9e3zTtHEfT8889r0aJFuvvuu7V582aNHTtWc+bMUVFRUZvn7d27V7fddptOP/30CFUKAAAARAeXxyNJMklyuDyqdbhV63DL6fYEHOfxeH3ftfSX19vCxbsxw9+uevjhh3X99ddrwYIFkqTHHntMK1as0BNPPKHbb7+9xXPcbrcuv/xyLV26VO+++67KysoiWDEAAADQe3m9XnmOhxqvpJFL3vB99/P5o3TF1IG+z3uOVuvsh05cNrZJlt2iU2fWq196zxh9MnTkyOFwaNOmTZo1a5Zvn9ls1qxZs7R+/fpWz/vZz36mrKwsXXvttZEoEwAAAEAnFNWZApo7dHeGjhyVlJTI7XYrOzs7YH92dra2bdvW4jnvvfee/vKXv2jLli0dukd9fb3q65sWtKqoqJAkOZ1OOZ3OzhUeAo33NrIG9Bw8LwgGzwuCwfOCYPC8RAf/qXOJNotG90vxfc5MiAn4+281eTVtcHqzaxRX1uur4mpJUp3DZfgz09H7Gz6tLhiVlZW68sor9fjjjyszM7ND5yxbtkxLly5ttn/VqlWKj48PdYlBW716tdEloAfheUEweF4QDJ4XBIPnpXerdkqNMSEvzqlvZzeN/NTvLtLK3YHHfztwnEOStNFs0lfFFknS9m3btLL8yzBV2zE1NTUdOs7QcJSZmSmLxaLCwsKA/YWFhcrJyWl2/K5du7R3717NmzfPt89z/GWxmJgYbd++XUOGDAk4Z/HixVq0aJHvc0VFhfLy8nTOOecoOTk5lD9OUJxOp1avXq3Zs2fLau0ZczBhHJ4XBIPnBcHgeUEweF6iw4FjNdLG9yRJg/v31dy5Y4K+xvDiavXdVqjt27frstlTNHZA89GlSGqcPdYeQ8NRbGysJk6cqDVr1vjacXs8Hq1Zs0YLFy5sdvyIESO0devWgH133nmnKisr9Zvf/EZ5eXnNzrHZbLLZbM32W63WbvEPdXepAz0DzwuCwfOCYPC8IBg8L71bbdMSR0qOj+3U3+sRfVM1pE+CVlZu09gB6YY/Lx29v+HT6hYtWqSrr75akyZN0uTJk7V8+XJVV1f7utddddVV6tevn5YtWya73a5Ro0YFnJ+amipJzfYDAAAACF5lXVM6SrYbHhciyvCf9tJLL1VxcbGWLFmigoICjRs3Tm+88YavScP+/ftlNhu+HBMAAAAQFfzDURLhKPIWLlzY4jQ6SVq7dm2b5z711FOhLwgAAACIUpV1TZ3dkuydmw5X43CppKJOx+qlqnqX0nrINMxuEY4AAAAAdA+hGDla/UWhfvDcFkkxcuce1rWnD2nvlG6B+WoAAAAAfPxHjhJt0TWWQjgCAAAA4BM4ctQzpsOFCuEIAAAAgE9FFDdkIBwBAAAA8PGfVpfMyBEAAACAaBXNrbwJRwAAAAB8ymv9Ro7iGDkCAAAAEKUqjoejJHuMLGaTwdVEFuEIAAAAgE/Z8XCUEmWjRhLhCAAAAMBxXq/XN60uNZ5wBAAAACBKVdW75PZ4JXVt5OisEVla+f+ma/FYl74xJjdU5YUd4QgAAACApMBmDKlxsZ2+TrLdqmFZicqJ71kjUIQjAAAAAJKkspro7VQnEY4AAAAAHFfhP3LUg0Z8QoVwBAAAAEBS4LS6rrxztLekWi9sPKj1hSbtLKwKRWkREV1L3gIAAABoVVmIwtEnB8t0x6tfSLJo2J5Sndw/LQTVhR8jRwAAAAAkndiQgWl1AAAAAKKUf0MGFoEFAAAAELUC3jmiIQMAAACAaFURoneOeirCEQAAAABJUlmtw7edGt/5RWB7KsIRAAAAAElN0+osZpMSYi0GVxN5hCMAAAAAkpoaMqTEWWUymQyuJvIIRwAAAAAkNY0cRWMbb4lwBAAAAECS2+NVZZ1LkpTcxXBkt1qUk2xTaqxX8T1oel6M0QUAAAAAMJ5/p7rULrbxnnNKjr52UoZWrlypuRP6dbW0iGHkCAAAAICO1fh1qmNaHQAAAIBo5R+O0hNsBlZiHMIRAAAAAB2t8g9H0TlyxDtHAAAAAEI6crRhT6n+8u4uFRSYFT+0WLNP6dvV8iKCcAQAAABApdVNDRm6OnJ0pLxWb35RJMms/aW1XawscphWBwAAAECl1fW+7bT4WAMrMQ7hCAAAAMAJI0eEIwAAAABRKvCdI8IRAAAAgChVWt0QjkwmKYV1jgAAAABEq8ZwlBJnVYwlOmNCdP7UAAAAAAIcOx6OonVKnUQ4AgAAAKKew+VRZb1LkpQepZ3qJMIRAAAAEPX8mzGkMXIEAAAAIFo1vm8kSRkhCEcD0uN18cR+mprl0dA+CV2+XqTEGF0AAAAAAGMdqw7tyNH4AWkalZuolSv3afqQjC5fL1IYOQIAAACi3FG/cMQ7RwAAAACiFgvANiAcAQAAAFHO/52jaA5HvHMEAAAARLmjVaENR69/elg/+eencrksKss8oKtnDO7yNSOBcAQAAABEueLKet92ZpKty9dze7yqdrglmeTyeLt8vUhhWh0AAAAQ5Uqq/MJRYvROqyMcAQAAAFGu+Hg4SrbHyBZjMbga4xCOAAAAgChXcnxaXZ8QTKnryQhHAAAAQBSrcbiOvx8kZSYSjgAAAABEqZLKpk51jBwBAAAAiFrFAc0YCEcAAAAAopR/G29GjgAAAABELf823n0YOQIAAAAQrQIXgA3NGkeT8tP120vHaMFJbp0xLDMk14yEGKMLAAAAAGCcwJEje0iu2S81TlmjcuTd79XAjPiQXDMSGDkCAAAAolg4Ro56KsIRAAAAEMX8R44yEnjnCAAAAECUamzlnRpvVWxMaOLB0ap6bd5fpj2VUpHfyFR3xztHAAAAQJTyer2+RWBDucbRe1+V6AfPbZEUo6SBhbr29MSQXTucGDkCAAAAolRVvUu1Trck2nhLhCMAAAAgahVWNE15y0kJTae6noxwBAAAAESpooo633ZWMiNHhCMAAAAgShX4haOcZEaOCEcAAABAlPKfVpdNOCIcAQAAANGq0G/kKJtpdYQjAAAAIFoVVfq9c5TEyBHrHAEAAABRyn9a3ZHyOh2tdgR8b5I0NCtRCbboiA3R8VMCAAAAaKagvGnk6JI/rm/xmJxku9b83xlREZB6/08IAAAAoEUJNku7xxRU1OnAsRqNyEnu8HXnjs7VzKHpWrVqlc6f1L8rJUYU4QgAAACIUr+7bIJe3nxQ9S5Ps+/e+rJQB4/VSpJS42KDuq7VYlaiLUZ2ixQb03PaHBCOAAAAgCg1PCdJi+eObPG7Lw5XNIWjeGskyzJMz4lxAAAAACKmtKahOUNCrEV2a/vT73oDRo4AAAAANHPseOe61PjgptRJ0pdHKrTik0PaecCsvgfKdOrgPqEuLywYOQIAAAAQwOPx6tjxkaP0hODD0Y7CSv1+7W69edCsTw9VhLq8sCEcAQAAAAhQUeeUx9uwndaJcNRTEY4AAAAABCj1Www2PUqaMUiEIwAAAAAnaJxSJzFyBAAAACCKlVY7fdvpnWjI0FMRjgAAAAAEOFbNyBEAAAAA+NY4kjrXra6nYp0jAAAAAAH83zl6efMhfbj7aLNjTCaTZp+crRlDMyNZWlgRjgAAAAAEqKhteuforS8LWz3umQ/3a8MdZ3dqodjuiGl1AAAAAAJMHpTeoeMcbo9KqhzN9qfFx2p8XoryE73qk9hzghMjRwAAAAACXDC+vyYNTA+YXudv2cptWn98ql18rKXZ9zNP6qNpg1K1cuVKfX1UTlhrDSXCEQAAAIBm8tLjlZce3+J3sTFNE9ASYntPpGBaHQAAAICg1Dhcvu24FkaOeirCEQAAAICg1DjckqRYizlgFKmn6z1jYAAAAAAiojEctTZq9L8dxXp41XaVlVmkvAJ9c0JeJMvrNMIRAAAAgKBU1zdMq0toJRyV1Tj0ycFySSaVVLfc1KE76j1jYAAAAAAionHkKN7Wu8ZaCEcAAAAAOszr9foaMrQ2ctRTEY4AAAAAdFi9yyOPt2G7N3WqkwhHAAAAAILQ+L6R1LvWOJIIRwAAAACC0Pi+kdT73jnqXT8NAAAAgLDyD0f/2XpEo7cXNTvG6fb4tmv9ju/uCEcAAAAAOszmt+iry+NVZZ2rjaOlbQWV4S4pZAhHAAAAADosPzNBN581RG9+Xiiv19viMcWV9ao4Hpr8R5G6O8IRAAAAgKD8aM4I/WjOiFa//8Par/TLN7ZLkvqlxkWqrC6jIQMAAACAkOrrF4j6pRGOAAAAAKBHIRwBAAAAgAhHAAAAAELM5deEwdWDGjIQjgAAAACE1JYD5b7tzfvLjCskSIQjAAAAABDhCAAAAAAkEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAAAkEY4AAAAAQBLhCAAAAECIjchN8m2fnJtsYCXBIRwBAAAACKlEW0zTtj2mjSO7F8IRAAAAAIhwBAAAAACSCEcAAAAAQqy02uHbPuq33d0RjgAAAACE1O7iat/2rqIqAysJDuEIAAAAAEQ4AgAAAABJhCMAAAAAkEQ4AgAAAABJhCMAAAAAkEQ4AgAAAABJhCMAAAAAkEQ4AgAAAABJhCMAAAAAIWYxm1rc7u4IRwAAAABCavyAVN/2xIFpxhUSpG4Rjh555BHl5+fLbrdrypQp2rBhQ6vHPv744zr99NOVlpamtLQ0zZo1q83jAQAAAKAjDA9Hzz//vBYtWqS7775bmzdv1tixYzVnzhwVFRW1ePzatWt12WWX6b///a/Wr1+vvLw8nXPOOTp06FCEKwcAAADQmxgejh5++GFdf/31WrBggU4++WQ99thjio+P1xNPPNHi8f/4xz900003ady4cRoxYoT+/Oc/y+PxaM2aNRGuHAAAAEBvYmg4cjgc2rRpk2bNmuXbZzabNWvWLK1fv75D16ipqZHT6VR6enq4ygQAAAAQhL0l1b7tPX7b3V2MkTcvKSmR2+1WdnZ2wP7s7Gxt27atQ9f4yU9+or59+wYELH/19fWqr6/3fa6oqJAkOZ1OOZ3OTlbedY33NrIG9Bw8LwgGzwuCwfOCYPC8oKOKKup824UVdYY/Mx29v6HhqKt+8Ytf6LnnntPatWtlt9tbPGbZsmVaunRps/2rVq1SfHx8uEts1+rVq40uAT0IzwuCwfOCYPC8IBg8L2jPvn1mNU5SKyos1MqVKw2tp6ampkPHGRqOMjMzZbFYVFhYGLC/sLBQOTk5bZ774IMP6he/+IXeeustjRkzptXjFi9erEWLFvk+V1RU+Jo4JCcnd+0H6AKn06nVq1dr9uzZslqthtWBnoHnBcHgeUEweF4QDJ4XdNSGf3+p9woPSJKysrM1d+54Q+tpnD3WHkPDUWxsrCZOnKg1a9Zo/vz5kuRrrrBw4cJWz/vVr36l++67T2+++aYmTZrU5j1sNptsNluz/VartVv8Q91d6kDPwPOCYPC8IBg8LwgGzwvaYzY3tTYwm0yGPy8dvb/h0+oWLVqkq6++WpMmTdLkyZO1fPlyVVdXa8GCBZKkq666Sv369dOyZcskSb/85S+1ZMkSPfPMM8rPz1dBQYEkKTExUYmJiYb9HAAAAAB6NsPD0aWXXqri4mItWbJEBQUFGjdunN544w1fk4b9+/cHJM8//OEPcjgcuuiiiwKuc/fdd+uee+6JZOkAAAAAehHDw5EkLVy4sNVpdGvXrg34vHfv3vAXBAAAACDqGL4ILAAAAAB0B4QjAAAAABDhCAAAAECIpSU0dYdLT4g1sJLgEI4AAAAAhNSQPk1dpIdm9ZyO0oQjAAAAABDhCAAAAAAkEY4AAAAAQBLhCAAAAECIfXKwzLe95UBZq8d1N4QjAAAAACHldHl92w6Xx8BKgkM4AgAAAAARjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAQIjlZ8Q3bWcmGFhJcAhHAAAAAEIqM8nm287y2+7uCEcAAAAAIMIRAAAAAEgiHAEAAAAIsRqHy2/bbWAlwSEcAQAAAAipLw5X+rY/O1RuYCXBIRwBAAAAgAhHAAAAACCJcAQAAAAAkghHAAAAACCJcAQAAAAAkghHAAAAACCJcAQAAAAAkghHAAAAACCJcAQAAAAAkghHAAAAAEJsTP8U3/a4vFTjCgkS4QgAAABASMXGmFvc7u56TqUAAAAAEEaEIwAAAAAQ4QgAAABAiBWU1/m2j/htd3eEIwAAAAAhdfBYrW/7QGmNgZUEh3AEAAAAACIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAACAEIuLNfttWwysJDiEIwAAAAAhdUrfFN/26H4pbRzZvRCOAAAAAECEIwAAAACQRDgCAAAAAEmEIwAAAAAhtqOw0re9raCyjSO7F8IRAAAAgJCqqHX5bTsNrCQ4hCMAAAAAEOEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAABAEuEIAAAAACQRjgAAAACEWHayzbedk2I3sJLgEI4AAAAAhFReerxve4DfdndHOAIAAAAAEY4AAAAAQBLhCAAAAECIeb3eFre7O8IRAAAAgJDatK/Mt/3R3mPGFRIkwhEAAAAAiHAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAIMSGZSf6tofnJBlYSXAIRwAAAABCKiXO2uJ2d0c4AgAAAAARjgAAAABAEuEIAAAAQIiV1zp922U1zjaO7F4IRwAAAABCamdhlW97R2GlgZUEh3AEAAAAACIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAIAkwhEAAAAASCIcAQAAAAixSflpvu3Jg9INrCQ4hCMAAAAAEOEIAAAAACQRjgAAAABAEuEIAAAAQIgdKK3xbe/32+7uCEcAAAAAQqqwot63XVBeZ2AlwSEcAQAAAIAIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAAJIIRwAAAAAgiXAEAAAAIMRS4mL8tq0GVhIcwhEAAACAkBqWneTbHp6T1MaR3QvhCAAAAABEOAIAAAAASYQjAAAAAJBEOAIAAAAQYp8dKvdtf3qwvI0juxfCEQAAAICQqnN6/LbdBlYSHMIRAAAAAIhwBAAAAACSCEcAAAAAIEmKaf8QAAAAIPzcbrecTqfRZSAEEmM86pdkkSSlxEp1dXVhvZ/VapXFYunydQhHAAAAMJTX61VBQYHKysqMLgUhMjPXqwnpWZKkOKtZe/bsCfs9U1NTlZOTI5PJ1OlrEI4AAABgqMZglJWVpfj4+C79covuobC8TmW1DklSoi1G/dLiw3Yvr9ermpoaFRUVSZJyc3M7fS3CEQAAAAzjdrt9wSgjI8PochAiMbVemY7PkIyxWmW328N6v7i4OElSUVGRsrKyOj3FjoYMAAAAMEzjO0bx8eEbWUB0aHyGuvLeGuEIAAAAhmMqXe8SG9P099MaE5nIEYpniHAEAAAAIKSsFrPfds8JvoQjAAAAoJvIz8/X8uXLjS4jJMbmpentN1ZIkvbu3SuTyaQtW7YYW1Q7CEcAAABAkEwmU5t/3XPPPZ267kcffaTvfe97XartzDPPDKglOztbF198sfbt29el63ZFXl6ejhw5olGjRhlWQ0cQjgAAAIAgHTlyxPfX8uXLlZycHLDvtttu8x3r9Xrlcrk6dN0+ffqEpDnF9ddfryNHjujw4cN69dVXdeDAAV1xxRVdvm5Hebxe37bXK1ksFuXk5Cgmpns3yyYcAQAAAEHKycnx/ZWSkiKTyeT7vG3bNiUlJek///mPJk6cKJvNpvfee0+7du3SN7/5TWVnZysxMVGnnnqq3nrrrYDrnjitzmQy6c9//rMuuOACxcfHa9iwYXrttdfarS8+Pl45OTnKzc3V1KlTtXDhQm3evNn3vdvt1rXXXqtBgwYpLi5Ow4cP129+85uAa6xdu1aTJ09WQkKCUlNTNWPGjIDRp1dffVUTJkyQ3W7X4MGDtXTpUl8IrHV4fMfVOtzNptWtXbtWJpNJa9as0aRJkxQfH6/p06dr+/btATW0dY9w6N7RDQAAAFFp3u/eU3FlfcTv2yfJpn//v9NCcq3bb79dDz74oAYPHqy0tDQdOHBAc+fO1X333Sebzaann35a8+bN0/bt2zVgwIBWr7N06VL96le/0gMPPKDf/e53uvzyy7Vv3z6lp6d3qI7S0lK98MILmjJlim+fx+NR//799eKLLyojI0Pvv/++vve97yk3N1eXXHKJXC6X5s+fr+uvv17PPvusHA6HNmzY4OsI9+677+qqq67Sb3/7W51++unatWuXbzrg3Xff3eE/ozvuuEMPPfSQ+vTpoxtuuEHf/e53tW7dupDeIxiEIwAAAHQ7xZX1KqioM7qMLvnZz36m2bNn+z6np6dr7Nixvs/33nuv/vWvf+m1117TwoULW73ONddco8suu0ySdP/99+u3v/2tNmzYoHPPPbfVcx599FH9+c9/ltfrVU1NjU466SS9+eabvu+tVquWLl3q+zxo0CCtX79eL7zwgi655BJVVFSovLxc559/voYMGSJJGjlypO/4pUuX6vbbb9fVV18tSRo8eLDuvfde/fjHPw4quNx3330644wzJDWEyfPOO091dXWy2+0hu0cwCEcAAADodvok2Xr8fSdNmhTwuaqqSvfcc49WrFihI0eOyOVyqba2Vvv372/zOmPGjPFtJyQkKDk5WUVFRW2ec/nll+uOO+6QJBUWFur+++/XOeeco02bNikpKUmS9Mgjj+iJJ57Q/v37VVtbK4fDoXHjxklqCHLXXHON5syZo9mzZ2vWrFm65JJLlJubK0n65JNPtG7dOt13332+e7rdbtXV1ammpkZSx9p3+/9sjdcuKirSgAED2r1HOBYO7hbh6JFHHtEDDzyggoICjR07Vr/73e80efLkVo9/8cUXddddd2nv3r0aNmyYfvnLX2ru3LkRrBgAAADhFKqpbUZKSEgI+Hzbbbdp9erVevDBBzV06FDFxcXpoosuksPhaPM6Vqs14LPJZJLH42nl6AYpKSkaOnSoJGno0KH6y1/+otzcXD3//PO67rrr9Nxzz+m2227TQw89pGnTpikpKUkPPPCAPvzwQ981nnzySd1yyy1644039Pzzz+vOO+/U6tWrNXXqVFVVVWnp0qW68MILm93bbrdL9R2bEun/szVO2Wv82dq9RxgYHo6ef/55LVq0SI899pimTJmi5cuXa86cOdq+fbuysrKaHf/+++/rsssu07Jly3T++efrmWee0fz587V58+Zu3xoQAAAA0WvdunW65pprdMEFF0hq+OV/7969Ebm3xWKRJNXW1vpqmT59um666SbfMbt27Wp23vjx4zV+/HgtXrxY06ZN0zPPPKOpU6dqwoQJ2r59uy+AhUMk7nEiw7vVPfzww7r++uu1YMECnXzyyXrssccUHx+vJ554osXjf/Ob3+jcc8/Vj370I40cOVL33nuvJkyYoN///vcRrhwAAADouGHDhunll1/Wli1b9Mknn+g73/lOuyNAnVVTU6OCggIVFBTok08+0Y033ii73a5zzjnHV8vGjRv15ptvaseOHbrrrrv00Ucf+c7fs2ePFi9erPXr12vfvn1atWqVdu7c6XvvaMmSJXr66ae1dOlSff755/ryyy/13HPP6c477wzZzxCJe5zI0HDkcDi0adMmzZo1y7fPbDZr1qxZWr9+fYvnrF+/PuB4SZozZ06rxwMAAADdwcMPP6y0tDRNnz5d8+bN05w5czRhwoSw3Ovxxx9Xbm6ucnNzddZZZ6mkpEQrV67U8OHDJUnf//73deGFF+rSSy/VlClTdPTo0YBRpPj4eG3btk3f+ta3dNJJJ+l73/uebr75Zn3/+9+X1PD79+uvv65Vq1bp1FNP1dSpU/XrX/9aAwcODNnPEIl7nMjQaXUlJSVyu93Kzs4O2J+dna1t27a1eE5BQUGLxxcUFLR4fH19ver95jxWVFRIkpxOp5xOZ1fK75LGextZA3oOnhcEg+cFweB5QTDC8bw4nU55vV55PJ6wjaKE21VXXaWrrrrKV//MmTPldrslKeBnGjBgQLN1jW688caA43bv3h3wuaXrlJaWNtvn7+2332611sZzrFar/vKXv+gvf/lLwPf33XefPB6P+vTpo5deeqnNa8yePTugG5//92az9MmBY5Iks1nqN2BAwM/S0p/RmDFjmu1r6x4t7fN6vXI6nb5phI06+swa/s5RuC1btiygTWGjVatWhaXDRbBWr15tdAnoQXheEAyeFwSD5wXBCOXzEhMTo5ycHFVVVbXbmAA9h8c/i7icqqgI/3+AcTgcqq2t1TvvvNNsodiGDnrtMzQcZWZmymKxqLCwMGB/YWGhcnJyWjwnJycnqOMXL16sRYsW+T5XVFQoLy9P55xzjpKTk7v4E3Se0+nU6tWrNXv27GYdSIAT8bwgGDwvCAbPC4IRjuelrq5OBw4cUGJiYtg6kCHykrxSpsejysoqpSQnyWLuWGvvrqirq1NcXJxmzpzZ7FlqnD3WHkPDUWxsrCZOnKg1a9Zo/vz5khqGw9asWdPqQljTpk3TmjVr9MMf/tC3b/Xq1Zo2bVqLx9tsNtlszfvVW63WbvF/At2lDvQMPC8IBs8LgsHzgmCE8nlxu90ymUwym80ymw3vFYYQMpmkGLNkMZsi8vfWbDbLZDK1+Hx29Hk1fFrdokWLdPXVV2vSpEmaPHmyli9frurqai1YsEBSwxzOfv36admyZZKkH/zgBzrjjDP00EMP6bzzztNzzz2njRs36k9/+pORPwYAAACAHs7wcHTppZequLhYS5YsUUFBgcaNG6c33njD13Rh//79AUlz+vTpeuaZZ3TnnXfqpz/9qYYNG6ZXXnmFNY4AAAAAdInh4UiSFi5c2Oo0urVr1zbbd/HFF+viiy8Oc1UAAAAAogkTOwEAAABAhCMAAAAAkEQ4AgAAANBJa9eulclkUllZmSTpqaeeUmpqqqE1dQXhCAAAAAiSyWRq86977rmnS9d+5ZVXgqohJiZGAwYM0KJFi1RfX9/pe3fVpZdeqh07dhh2/67qFg0ZAAAAgJ7kyJEjvu3nn39eS5Ys0fbt2337EhMTI1LHk08+qXPPPVdOp1OffPKJFixYoISEBN17770Ruf+J4uLiFBcXZ8i9Q4GRIwAAACBIOTk5vr9SUlJkMpkC9j333HMaOXKk7Ha7RowYoUcffdR3rsPh0MKFC5Wbmyu73a6BAwf61vTMz8+XJF1wwQUymUy+z61JTU1VTk6O8vLydP755+ub3/ymNm/e7Pt+165d+uY3v6ns7GwlJibq1FNP1VtvvRVwjUcffVTDhg2T3W5Xdna2LrroIt93Ho9Hy5Yt06BBgxQXF6exY8fqn//8Z6v1nDit7he/+IUmTJigv/3tb8rPz1dKSoq+/e1vq7KystP3CCdGjgAAAIAQ+sc//qElS5bo97//vcaPH6+PP/5Y119/vRISEnT11Vfrt7/9rV577TW98MILGjBggA4cOKADBw5Ikj766CNlZWX5RoQsFkuH77tjxw69/fbbuuaaa3z7qqqqNHfuXN13332y2Wx6+umnNW/ePG3fvl0DBgzQxo0bdcstt+hvf/ubpk+frtLSUr377ru+85ctW6a///3veuyxxzRs2DC98847uuKKK9SnTx+dccYZHapr165deuWVV/T666/r2LFjuuSSS/SLX/xC9913X8juESqEIwAAAHRLf353t/787p52jxvVL1l/vvrUgH3X/fUjfXaoot1zrzt9kK47fXCna2zJ3XffrYceekgXXnihJGnQoEH64osv9Mc//lFXX3219u/fr2HDhum0006TyWTSwIEDfef26dNHUtOIUHsuu+wyWSwWuVwu1dfX6/zzz9fixYt9348dO1Zjx471fb733nv1r3/9S6+99poWLlyo/fv3KyEhQeeff76SkpI0cOBAjR8/XpJUX1+v+++/X2+99ZamTZsmSRo8eLDee+89/fGPf+xwcPF4PHrqqaeUlJQkSbryyiu1Zs0a3XfffSG7R6gQjgAAANAtVda5VFBR1+5xuan2ZvuOVjs6dG5lnatTtbWmurpau3bt0rXXXqvrr7/et9/lciklJUWSdM0112j27NkaPny4zj33XJ1//vk655xzOnW/X//615o1a5bcbre++uorLVq0SFdeeaWee+45SQ0jR/fcc49WrFihI0eOyOVyqba2Vvv375ckzZ49WwMHDtTgwYN17rnn6txzz9UFF1yg+Ph4ffXVV6qpqdHs2bMD7ulwOHwBqiPy8/N9wUiScnNzVVRUJEkhu0eoEI4AAADQLSXZY5ST3Dz4nCgjIbbFfR05N8ke2l+Hq6qqJEmPP/64pkyZEvBd4xS5CRMmaM+ePfrPf/6jt956S5dccolmzZrVqfdscnJyNHToUEnS8OHDVVlZqcsuu0w///nPNXToUN12221avXq1HnzwQQ0dOlRxcXG66KKL5HA4JElJSUnavHmz1q5dq1WrVmnJkiW655579NFHH/l+lhUrVqhfv34B97XZbB2u0Wq1Bnw2mUzyeDySFLJ7hArhCAAAAN3SdacP7vSUtxOn2UVKdna2+vbtq927d+vyyy9v9bjk5GRdeumluvTSS3XRRRfp3HPPVWlpqdLT02W1WuV2uzt1/8YAVltbK0lat26drrnmGl1wwQWSGsLI3r17A86JiYnRrFmzNGvWLN19991KTU3V22+/rdmzZ8tms2n//v1hm9528sknh/0ewSAcAQAAACG0dOlS3XLLLUpJSdG5556r+vp6bdy4UceOHdOiRYv08MMPKzc3V+PHj5fZbNaLL76onJwcX5e3/Px8rVmzRjNmzJDNZlNaWlqr9yorK1NBQYE8Ho927typn/3sZzrppJM0cuRISdKwYcP08ssva968eTKZTLrrrrt8ozaS9Prrr2v37t2aOXOm0tLStHLlSnk8Hg0fPlxJSUm67bbbdOutt8rj8ei0005TeXm51q1bp+TkZF199dVd/rOKxD2CQTgCAAAAQui6665TfHy8HnjgAf3oRz9SQkKCRo8erR/+8IeSGgLBr371K+3cuVMWi0WnnnqqVq5cKbO5YZWdhx56SIsWLdLjjz+ufv36NRvp8bdgwQJJ8rUSnzlzpu6//37FxDT8mv/www/ru9/9rqZPn67MzEz95Cc/UUVFU6OK1NRUvfzyy7rnnntUV1enYcOG6dlnn9Upp5wiqaGBQ58+fbRs2TLt3r1bqampmjBhgn7605+G7M8rEvfoKJPX6/VG/K4GqqioUEpKisrLy5WcnGxYHU6nUytXrtTcuXObzcMETsTzgmDwvCAYPC8IRjiel7q6Ou3Zs0eDBg2S3d7+O0LoOTwejyoqKpScnOwLfuHU1rPU0QzAIrAAAAAAIMIRAAAAAEgiHAEAAACAJMIRAAAAAEgiHAEAAACAJMIRAAAAuoEoa6CMMAjFM0Q4AgAAgGEaW4LX1NQYXAl6usZnqCtt5lkEFgAAAIaxWCxKTU1VUVGRJCk+Pl4mk8ngqhAKHo9HDodDdXV1YV3nyOv1qqamRkVFRUpNTZXFYun0tQhHAAAAMFROTo4k+QISegev16va2lrFxcVFJPCmpqb6nqXOIhwBAADAUCaTSbm5ucrKypLT6TS6HISI0+nUO++8o5kzZ3ZpqltHWK3WLo0YNSIcAQAAoFuwWCwh+QUX3YPFYpHL5ZLdbg97OAoVGjIAAAAAgAhHAAAAACCJcAQAAAAAkqLwnaPGxaEqKioMrcPpdKqmpkYVFRU9Zg4mjMPzgmDwvCAYPC8IBs8LgtGdnpfG3/3bWyg26sJRZWWlJCkvL8/gSgAAAABEUmVlpVJSUlr93uRtLz71Mh6PR4cPH1ZSUpKhC4xVVFQoLy9PBw4cUHJysmF1oGfgeUEweF4QDJ4XBIPnBcHoTs+L1+tVZWWl+vbt2+aCtFE3cmQ2m9W/f3+jy/BJTk42/GFBz8HzgmDwvCAYPC8IBs8LgtFdnpe2Rowa0ZABAAAAAEQ4AgAAAABJhCPD2Gw23X333bLZbEaXgh6A5wXB4HlBMHheEAyeFwSjJz4vUdeQAQAAAABawsgRAAAAAIhwBAAAAACSCEcAAAAAIIlwBAAAAACSCEdh9cgjjyg/P192u11TpkzRhg0b2jz+xRdf1IgRI2S32zV69GitXLkyQpWiOwjmeXn88cd1+umnKy0tTWlpaZo1a1a7zxd6l2D//dLoueeek8lk0vz588NbILqVYJ+XsrIy3XzzzcrNzZXNZtNJJ53E/ydFkWCfl+XLl2v48OGKi4tTXl6ebr31VtXV1UWoWhjpnXfe0bx589S3b1+ZTCa98sor7Z6zdu1aTZgwQTabTUOHDtVTTz0V9jqDQTgKk+eff16LFi3S3Xffrc2bN2vs2LGaM2eOioqKWjz+/fff12WXXaZrr71WH3/8sebPn6/58+frs88+i3DlMEKwz8vatWv/fzv3HtPU+YcB/CmFUi4liAxaFsSAm5LOuYhoEBeDMsExx7IYms00JdGxzaJbdmUzS4lXZphZFMVMHLjMO5kLQSZKVzLHWLIoLCzDKpfOXURnXDLEsbb0/f1lt2pdbH+2p+DzSfpH377nnOc035Tz5T0tnnvuOVgsFnR2diI1NRVLlizBr7/+GuTkJAVf6+Umm82GN954A48//niQklIo8LVe7HY7nnjiCdhsNjQ2NsJqtWLPnj148MEHg5ycpOBrvRw4cAAVFRUwmUzo7e3F3r17cfjwYbz77rtBTk5SGBkZwaxZs7Bz5867mj84OIiioiLk5eWhu7sbr776KlatWoXW1tYAJ/WBoICYO3euMBqN7udjY2MiJSVFbNmyxev8kpISUVRU5DE2b9488eKLLwY0J4UGX+vlVk6nU6hUKrFv375ARaQQ4k+9OJ1OMX/+fFFXVycMBoMoLi4OQlIKBb7WS21trUhPTxd2uz1YESmE+FovRqNRLFq0yGPstddeE7m5uQHNSaEHgDh27Nh/znnrrbeEVqv1GNPpdKKgoCCAyXzDlaMAsNvtOHPmDPLz891jYWFhyM/PR2dnp9dtOjs7PeYDQEFBwR3n08ThT73c6saNG3A4HEhISAhUTAoR/tbL+vXrkZSUhJUrVwYjJoUIf+qlqakJOTk5MBqNSE5OxiOPPILNmzdjbGwsWLFJIv7Uy/z583HmzBn3rXcDAwNoaWnBk08+GZTMNL6Mh+vdcKkDTERXr17F2NgYkpOTPcaTk5Nx7tw5r9sMDQ15nT80NBSwnBQa/KmXW7399ttISUm57QOHJh5/6uXrr7/G3r170d3dHYSEFEr8qZeBgQF8+eWXWLFiBVpaWtDX14fVq1fD4XDAZDIFIzZJxJ96ef7553H16lUsWLAAQgg4nU689NJLvK2OvLrT9e6ff/6Jv/76C1FRURIl+wdXjojGuaqqKhw6dAjHjh2DUqmUOg6FmOHhYej1euzZsweJiYlSx6FxwOVyISkpCR999BGysrKg0+mwbt067N69W+poFILa29uxefNm7Nq1C2fPnsVnn32G48ePY8OGDVJHI/ILV44CIDExEXK5HJcvX/YYv3z5MtRqtddt1Gq1T/Np4vCnXm6qrq5GVVUV2tra8OijjwYyJoUIX+ulv78fNpsNy5Ytc4+5XC4AQHh4OKxWKzIyMgIbmiTjz+eLRqNBREQE5HK5eywzMxNDQ0Ow2+1QKBQBzUzS8ade3nvvPej1eqxatQoAMHPmTIyMjKCsrAzr1q1DWBj/D0//uNP1blxcXEisGgFcOQoIhUKBrKwsmM1m95jL5YLZbEZOTo7XbXJycjzmA8CpU6fuOJ8mDn/qBQC2bt2KDRs24MSJE5gzZ04wolII8LVeZsyYgZ6eHnR3d7sfTz/9tPuXglJTU4MZn4LMn8+X3Nxc9PX1uZtoADh//jw0Gg0bownOn3q5cePGbQ3QzcZaCBG4sDQujYvrXal/EWKiOnTokIiMjBQNDQ3ixx9/FGVlZSI+Pl4MDQ0JIYTQ6/WioqLCPb+jo0OEh4eL6upq0dvbK0wmk4iIiBA9PT1SnQIFka/1UlVVJRQKhWhsbBSXLl1yP4aHh6U6BQoiX+vlVvy1uvuLr/Vy8eJFoVKpRHl5ubBaraK5uVkkJSWJjRs3SnUKFES+1ovJZBIqlUocPHhQDAwMiJMnT4qMjAxRUlIi1SlQEA0PD4uuri7R1dUlAIht27aJrq4u8dNPPwkhhKioqBB6vd49f2BgQERHR4s333xT9Pb2ip07dwq5XC5OnDgh1Snchs1RAO3YsUNMmTJFKBQKMXfuXPHtt9+6X1u4cKEwGAwe848cOSIefvhhoVAohFarFcePHw9yYpKSL/WSlpYmANz2MJlMwQ9OkvD18+Xf2Bzdf3ytl2+++UbMmzdPREZGivT0dLFp0ybhdDqDnJqk4ku9OBwOUVlZKTIyMoRSqRSpqali9erV4o8//gh+cAo6i8Xi9XrkZo0YDAaxcOHC27Z57LHHhEKhEOnp6aK+vj7ouf+LTAiueRIREREREfE7R0RERERERGBzREREREREBIDNEREREREREQA2R0RERERERADYHBEREREREQFgc0RERERERASAzREREREREREANkdERHQfkclk+Pzzz+/5XCIimhjYHBERkSRKS0shk8kgk8mgUCgwbdo0rF+/Hk6nM2DHvHTpEpYuXXrP5xIR0cQQLnUAIiK6fxUWFqK+vh5///03WlpaYDQaERERgXfeecdjnt1uh0Kh+L+Pp1arAzKXiIgmBq4cERGRZCIjI6FWq5GWloaXX34Z+fn5aGpqQmlpKZ555hls2rQJKSkpmD59OgDg559/RklJCeLj45GQkIDi4mLYbDaPfX788cfQarWIjIyERqNBeXm5+7V/3ypnt9tRXl4OjUYDpVKJtLQ0bNmyxetcAOjp6cGiRYsQFRWFyZMno6ysDNevX3e/fjNzdXU1NBoNJk+eDKPRCIfDce/fOCIiCgg2R0REFDKioqJgt9sBAGazGVarFadOnUJzczMcDgcKCgqgUqlw+vRpdHR0IDY2FoWFhe5tamtrYTQaUVZWhp6eHjQ1NWHatGlej7V9+3Y0NTXhyJEjsFqt2L9/P6ZOnep17sjICAoKCjBp0iR89913OHr0KNra2jwaLwCwWCzo7++HxWLBvn370NDQgIaGhnv2/hARUWDxtjoiIpKcEAJmsxmtra1Ys2YNfv/9d8TExKCurs59O92nn34Kl8uFuro6yGQyAEB9fT3i4+PR3t6OJUuWYOPGjXj99dfxyiuvuPednZ3t9ZgXL17EQw89hAULFkAmkyEtLe2O+Q4cOIDR0VF88skniImJAQDU1NRg2bJleP/995GcnAwAmDRpEmpqaiCXyzFjxgwUFRXBbDbjhRdeuCfvExERBRZXjoiISDLNzc2IjY2FUqnE0qVLodPpUFlZCQCYOXOmx/eMvv/+e/T19UGlUiE2NhaxsbFISEjA6Ogo+vv7ceXKFfz2229YvHjxXR27tLQU3d3dmD59OtauXYuTJ0/ecW5vby9mzZrlbowAIDc3Fy6XC1ar1T2m1Wohl8vdzzUaDa5cuXK3bwcREUmMK0dERCSZvLw81NbWQqFQICUlBeHh//xZ+ncjAgDXr19HVlYW9u/ff9t+HnjgAYSF+fb/vtmzZ2NwcBBffPEF2traUFJSgvz8fDQ2Nvp3MgAiIiI8nstkMrhcLr/3R0REwcXmiIiIJBMTE3PH7wTdavbs2Th8+DCSkpIQFxfndc7UqVNhNpuRl5d3V/uMi4uDTqeDTqfD8uXLUVhYiGvXriEhIcFjXmZmJhoaGjAyMuJu2jo6OhAWFub+sQgiIhr/eFsdERGNCytWrEBiYiKKi4tx+vRpDA4Oor29HWvXrsUvv/wCAKisrMQHH3yA7du348KFCzh79ix27NjhdX/btm3DwYMHce7cOZw/fx5Hjx6FWq1GfHy812MrlUoYDAb88MMPsFgsWLNmDfR6vfv7RkRENP6xOSIionEhOjoaX331FaZMmYJnn30WmZmZWLlyJUZHR90rSQaDAR9++CF27doFrVaLp556ChcuXPC6P5VKha1bt2LOnDnIzs6GzWZDS0uL19vzoqOj0draimvXriE7OxvLly/H4sWLUVNTE9BzJiKi4JIJIYTUIYiIiIiIiKTGlSMiIiIiIiKwOSIiIiIiIgLA5oiIiIiIiAgAmyMiIiIiIiIAbI6IiIiIiIgAsDkiIiIiIiICwOaIiIiIiIgIAJsjIiIiIiIiAGyOiIiIiIiIALA5IiIiIiIiAsDmiIiIiIiICACbIyIiIiIiIgDA/wC1Bj3B7j4w4QAAAABJRU5ErkJggg==",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_prc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
"plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
"plt.legend(loc='lower right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "gpdsFyp64DhY"
},
"source": [
"It looks like the precision is relatively high, but the recall and the area under the ROC curve (AUC) aren't as high as you might like. Classifiers often face challenges when trying to maximize both precision and recall, which is especially true when working with imbalanced datasets. It is important to consider the costs of different types of errors in the context of the problem you care about. In this example, a false negative (a fraudulent transaction is missed) may have a financial cost, while a false positive (a transaction is incorrectly flagged as fraudulent) may decrease user happiness."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "cveQoiMyGQCo"
},
"source": [
"## Class weights"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ePGp6GUE1WfH"
},
"source": [
"### Calculate class weights\n",
"\n",
"The goal is to identify fraudulent transactions, but you don't have very many of those positive samples to work with, so you would want to have the classifier heavily weight the few examples that are available. You can do this by passing Keras weights for each class through a parameter. These will cause the model to \"pay more attention\" to examples from an under-represented class. Note, however, that this does not increase in any way the amount of information of your dataset. In the end, using class weights is more or less equivalent to changing the output bias or to changing the threshold. Let's see how it works out."
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.916149Z",
"iopub.status.busy": "2024-08-20T01:25:11.915855Z",
"iopub.status.idle": "2024-08-20T01:25:11.920630Z",
"shell.execute_reply": "2024-08-20T01:25:11.920025Z"
},
"id": "qjGWErngGny7"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Weight for class 0: 0.50\n",
"Weight for class 1: 289.44\n"
]
}
],
"source": [
"# Scaling by total/2 helps keep the loss to a similar magnitude.\n",
"# The sum of the weights of all examples stays the same.\n",
"weight_for_0 = (1 / neg) * (total / 2.0)\n",
"weight_for_1 = (1 / pos) * (total / 2.0)\n",
"\n",
"class_weight = {0: weight_for_0, 1: weight_for_1}\n",
"\n",
"print('Weight for class 0: {:.2f}'.format(weight_for_0))\n",
"print('Weight for class 1: {:.2f}'.format(weight_for_1))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Mk1OOE2ZSHzy"
},
"source": [
"### Train a model with class weights\n",
"\n",
"Now try re-training and evaluating the model with class weights to see how that affects the predictions.\n",
"\n",
"Note: Using `class_weights` changes the range of the loss. This may affect the stability of the training depending on the optimizer. Optimizers whose step size is dependent on the magnitude of the gradient, like `tf.keras.optimizers.SGD`, may fail. The optimizer used here, `tf.keras.optimizers.Adam`, is unaffected by the scaling change. Also note that because of the weighting, the total losses are not comparable between the two models."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:11.923998Z",
"iopub.status.busy": "2024-08-20T01:25:11.923453Z",
"iopub.status.idle": "2024-08-20T01:25:24.880463Z",
"shell.execute_reply": "2024-08-20T01:25:24.879805Z"
},
"id": "UJ589fn8ST3x"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/100\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
" super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m6:00\u001b[0m 4s/step - Brier score: 4.8176e-04 - accuracy: 0.9995 - auc: 0.9415 - cross entropy: 0.0029 - fn: 23.0000 - fp: 7.0000 - loss: 1.5095 - prc: 0.8239 - precision: 0.9205 - recall: 0.7788 - tn: 58899.0000 - tp: 81.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m23/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 9.4502e-04 - accuracy: 0.9990 - auc: 0.8820 - cross entropy: 0.0060 - fn: 60.4783 - fp: 27.9565 - loss: 2.2363 - prc: 0.6085 - precision: 0.7546 - recall: 0.5922 - tn: 81367.9141 - tp: 81.6522"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m46/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0012 - accuracy: 0.9987 - auc: 0.8544 - cross entropy: 0.0076 - fn: 96.3696 - fp: 53.5652 - loss: 2.2360 - prc: 0.4991 - precision: 0.6450 - recall: 0.4987 - tn: 104854.6484 - tp: 85.4130 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m71/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0014 - accuracy: 0.9985 - auc: 0.8427 - cross entropy: 0.0087 - fn: 131.7324 - fp: 85.3803 - loss: 2.1665 - prc: 0.4314 - precision: 0.5737 - recall: 0.4516 - tn: 130377.8438 - tp: 95.0423"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0015 - accuracy: 0.9983 - auc: 0.8392 - cross entropy: 0.0094 - fn: 155.4556 - fp: 116.7444 - loss: 2.0937 - prc: 0.3955 - precision: 0.5307 - recall: 0.4320 - tn: 149747.2500 - tp: 103.8333"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 47ms/step - Brier score: 0.0015 - accuracy: 0.9983 - auc: 0.8391 - cross entropy: 0.0094 - fn: 156.5934 - fp: 118.4505 - loss: 2.0900 - prc: 0.3940 - precision: 0.5288 - recall: 0.4313 - tn: 150723.1719 - tp: 104.3516 - val_Brier score: 6.9626e-04 - val_accuracy: 0.9993 - val_auc: 0.9530 - val_cross entropy: 0.0072 - val_fn: 25.0000 - val_fp: 8.0000 - val_loss: 0.0072 - val_prc: 0.7354 - val_precision: 0.8769 - val_recall: 0.6951 - val_tn: 45479.0000 - val_tp: 57.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 56ms/step - Brier score: 0.0049 - accuracy: 0.9946 - auc: 0.7400 - cross entropy: 0.0260 - fn: 4.0000 - fp: 7.0000 - loss: 2.9107 - prc: 0.2079 - precision: 0.2222 - recall: 0.3333 - tn: 2035.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0033 - accuracy: 0.9963 - auc: 0.8914 - cross entropy: 0.0189 - fn: 27.8800 - fp: 65.8800 - loss: 1.3344 - prc: 0.3205 - precision: 0.2963 - recall: 0.4811 - tn: 26501.4805 - tp: 28.7600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0033 - accuracy: 0.9964 - auc: 0.8921 - cross entropy: 0.0191 - fn: 49.8200 - fp: 138.5000 - loss: 1.2122 - prc: 0.3214 - precision: 0.2832 - recall: 0.4993 - tn: 51982.7812 - tp: 52.9000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0034 - accuracy: 0.9963 - auc: 0.8910 - cross entropy: 0.0194 - fn: 67.9605 - fp: 225.6711 - loss: 1.1202 - prc: 0.3229 - precision: 0.2700 - recall: 0.5171 - tn: 78475.9844 - tp: 78.3816"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0034 - accuracy: 0.9963 - auc: 0.8909 - cross entropy: 0.0196 - fn: 77.0110 - fp: 278.7912 - loss: 1.0765 - prc: 0.3266 - precision: 0.2644 - recall: 0.5273 - tn: 93691.4688 - tp: 93.2967 - val_Brier score: 9.0370e-04 - val_accuracy: 0.9992 - val_auc: 0.9600 - val_cross entropy: 0.0106 - val_fn: 13.0000 - val_fp: 23.0000 - val_loss: 0.0106 - val_prc: 0.7694 - val_precision: 0.7500 - val_recall: 0.8415 - val_tn: 45464.0000 - val_tp: 69.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0034 - accuracy: 0.9971 - auc: 0.9997 - cross entropy: 0.0202 - fn: 0.0000e+00 - fp: 6.0000 - loss: 0.0218 - prc: 0.6819 - precision: 0.3333 - recall: 1.0000 - tn: 2039.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0045 - accuracy: 0.9952 - auc: 0.9069 - cross entropy: 0.0250 - fn: 16.5600 - fp: 118.1600 - loss: 0.6688 - prc: 0.3881 - precision: 0.1880 - recall: 0.6329 - tn: 26464.9199 - tp: 24.3600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m49/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0048 - accuracy: 0.9948 - auc: 0.8999 - cross entropy: 0.0263 - fn: 33.6327 - fp: 247.6939 - loss: 0.7407 - prc: 0.3902 - precision: 0.1846 - recall: 0.6269 - tn: 50865.1016 - tp: 53.5714"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m74/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0050 - accuracy: 0.9945 - auc: 0.9013 - cross entropy: 0.0273 - fn: 48.2432 - fp: 397.2162 - loss: 0.7345 - prc: 0.3962 - precision: 0.1818 - recall: 0.6366 - tn: 76269.3516 - tp: 85.1892"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0052 - accuracy: 0.9943 - auc: 0.9018 - cross entropy: 0.0280 - fn: 56.4945 - fp: 508.4615 - loss: 0.7222 - prc: 0.3978 - precision: 0.1789 - recall: 0.6450 - tn: 93469.3984 - tp: 106.2198 - val_Brier score: 0.0016 - val_accuracy: 0.9987 - val_auc: 0.9681 - val_cross entropy: 0.0158 - val_fn: 11.0000 - val_fp: 49.0000 - val_loss: 0.0158 - val_prc: 0.7802 - val_precision: 0.5917 - val_recall: 0.8659 - val_tn: 45438.0000 - val_tp: 71.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 53ms/step - Brier score: 0.0085 - accuracy: 0.9912 - auc: 0.6689 - cross entropy: 0.0424 - fn: 3.0000 - fp: 15.0000 - loss: 2.0722 - prc: 0.1273 - precision: 0.0625 - recall: 0.2500 - tn: 2029.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0079 - accuracy: 0.9913 - auc: 0.8713 - cross entropy: 0.0397 - fn: 13.6154 - fp: 227.8462 - loss: 0.6866 - prc: 0.3892 - precision: 0.1043 - recall: 0.6371 - tn: 27379.6914 - tp: 26.8462"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0080 - accuracy: 0.9911 - auc: 0.8882 - cross entropy: 0.0402 - fn: 26.9412 - fp: 456.1961 - loss: 0.6336 - prc: 0.3857 - precision: 0.1077 - recall: 0.6588 - tn: 52708.6484 - tp: 56.2157"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0081 - accuracy: 0.9908 - auc: 0.8950 - cross entropy: 0.0408 - fn: 40.5195 - fp: 710.8961 - loss: 0.6246 - prc: 0.3944 - precision: 0.1111 - recall: 0.6743 - tn: 79028.7109 - tp: 91.8701"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0082 - accuracy: 0.9907 - auc: 0.8985 - cross entropy: 0.0412 - fn: 46.3956 - fp: 854.7033 - loss: 0.6114 - prc: 0.3998 - precision: 0.1116 - recall: 0.6828 - tn: 93128.9766 - tp: 110.4945 - val_Brier score: 0.0025 - val_accuracy: 0.9979 - val_auc: 0.9732 - val_cross entropy: 0.0218 - val_fn: 10.0000 - val_fp: 86.0000 - val_loss: 0.0218 - val_prc: 0.7647 - val_precision: 0.4557 - val_recall: 0.8780 - val_tn: 45401.0000 - val_tp: 72.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 5/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 0.0128 - accuracy: 0.9844 - auc: 0.9453 - cross entropy: 0.0542 - fn: 2.0000 - fp: 30.0000 - loss: 1.0314 - prc: 0.7055 - precision: 0.1429 - recall: 0.7143 - tn: 2011.0000 - tp: 5.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0110 - accuracy: 0.9872 - auc: 0.8851 - cross entropy: 0.0512 - fn: 18.6538 - fp: 337.9231 - loss: 0.8869 - prc: 0.5076 - precision: 0.1168 - recall: 0.6958 - tn: 27249.0000 - tp: 42.4231"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0113 - accuracy: 0.9868 - auc: 0.8933 - cross entropy: 0.0523 - fn: 32.3922 - fp: 688.2941 - loss: 0.7917 - prc: 0.4746 - precision: 0.1062 - recall: 0.6978 - tn: 52452.0977 - tp: 75.2157"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0116 - accuracy: 0.9864 - auc: 0.9012 - cross entropy: 0.0537 - fn: 42.0263 - fp: 1062.8158 - loss: 0.7068 - prc: 0.4476 - precision: 0.0985 - recall: 0.7073 - tn: 77638.3828 - tp: 104.7763"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0118 - accuracy: 0.9862 - auc: 0.9054 - cross entropy: 0.0546 - fn: 46.5934 - fp: 1299.8242 - loss: 0.6663 - prc: 0.4400 - precision: 0.0955 - recall: 0.7156 - tn: 92670.6953 - tp: 123.4615 - val_Brier score: 0.0040 - val_accuracy: 0.9962 - val_auc: 0.9780 - val_cross entropy: 0.0291 - val_fn: 10.0000 - val_fp: 161.0000 - val_loss: 0.0291 - val_prc: 0.7608 - val_precision: 0.3090 - val_recall: 0.8780 - val_tn: 45326.0000 - val_tp: 72.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0153 - accuracy: 0.9824 - auc: 0.9886 - cross entropy: 0.0677 - fn: 1.0000 - fp: 35.0000 - loss: 0.2406 - prc: 0.4593 - precision: 0.0789 - recall: 0.7500 - tn: 2009.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0145 - accuracy: 0.9830 - auc: 0.9396 - cross entropy: 0.0664 - fn: 10.3077 - fp: 469.1538 - loss: 0.3735 - prc: 0.4237 - precision: 0.0732 - recall: 0.7957 - tn: 27130.7305 - tp: 37.8077"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0148 - accuracy: 0.9826 - auc: 0.9319 - cross entropy: 0.0674 - fn: 20.1731 - fp: 943.4423 - loss: 0.4088 - prc: 0.4155 - precision: 0.0727 - recall: 0.7897 - tn: 53234.8086 - tp: 73.5769"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0151 - accuracy: 0.9822 - auc: 0.9298 - cross entropy: 0.0683 - fn: 28.7051 - fp: 1441.4359 - loss: 0.4091 - prc: 0.4066 - precision: 0.0700 - recall: 0.7885 - tn: 79320.6562 - tp: 105.2051"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0152 - accuracy: 0.9821 - auc: 0.9291 - cross entropy: 0.0687 - fn: 33.1978 - fp: 1695.3627 - loss: 0.4118 - prc: 0.4045 - precision: 0.0694 - recall: 0.7888 - tn: 92289.2891 - tp: 122.7253 - val_Brier score: 0.0054 - val_accuracy: 0.9945 - val_auc: 0.9816 - val_cross entropy: 0.0356 - val_fn: 9.0000 - val_fp: 243.0000 - val_loss: 0.0356 - val_prc: 0.7555 - val_precision: 0.2310 - val_recall: 0.8902 - val_tn: 45244.0000 - val_tp: 73.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0185 - accuracy: 0.9766 - auc: 0.9472 - cross entropy: 0.0735 - fn: 1.0000 - fp: 47.0000 - loss: 0.6100 - prc: 0.5083 - precision: 0.0962 - recall: 0.8333 - tn: 1995.0000 - tp: 5.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0178 - accuracy: 0.9786 - auc: 0.9611 - cross entropy: 0.0777 - fn: 8.0769 - fp: 582.1923 - loss: 0.3827 - prc: 0.4854 - precision: 0.0874 - recall: 0.8662 - tn: 27005.5000 - tp: 52.2308"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m52/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0183 - accuracy: 0.9780 - auc: 0.9563 - cross entropy: 0.0797 - fn: 15.9038 - fp: 1197.8846 - loss: 0.3620 - prc: 0.4344 - precision: 0.0749 - recall: 0.8524 - tn: 52972.3828 - tp: 85.8269"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m78/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0186 - accuracy: 0.9775 - auc: 0.9515 - cross entropy: 0.0810 - fn: 24.1410 - fp: 1838.6025 - loss: 0.3647 - prc: 0.4082 - precision: 0.0687 - recall: 0.8417 - tn: 78914.1797 - tp: 119.0769"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0187 - accuracy: 0.9773 - auc: 0.9501 - cross entropy: 0.0816 - fn: 28.1758 - fp: 2161.0769 - loss: 0.3649 - prc: 0.4001 - precision: 0.0667 - recall: 0.8385 - tn: 91815.3203 - tp: 136.0000 - val_Brier score: 0.0073 - val_accuracy: 0.9918 - val_auc: 0.9819 - val_cross entropy: 0.0436 - val_fn: 8.0000 - val_fp: 366.0000 - val_loss: 0.0436 - val_prc: 0.6999 - val_precision: 0.1682 - val_recall: 0.9024 - val_tn: 45121.0000 - val_tp: 74.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 8/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0192 - accuracy: 0.9756 - auc: 0.9982 - cross entropy: 0.0893 - fn: 0.0000e+00 - fp: 50.0000 - loss: 0.0488 - prc: 0.3458 - precision: 0.0566 - recall: 1.0000 - tn: 1995.0000 - tp: 3.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0217 - accuracy: 0.9733 - auc: 0.9457 - cross entropy: 0.0941 - fn: 10.2400 - fp: 711.0800 - loss: 0.3433 - prc: 0.2986 - precision: 0.0457 - recall: 0.7746 - tn: 25870.6797 - tp: 32.0000 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0223 - accuracy: 0.9725 - auc: 0.9500 - cross entropy: 0.0961 - fn: 18.1800 - fp: 1443.5800 - loss: 0.3386 - prc: 0.3025 - precision: 0.0454 - recall: 0.7858 - tn: 50694.1406 - tp: 68.1000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0228 - accuracy: 0.9720 - auc: 0.9513 - cross entropy: 0.0976 - fn: 25.8553 - fp: 2231.9211 - loss: 0.3350 - prc: 0.3089 - precision: 0.0457 - recall: 0.7963 - tn: 76483.5938 - tp: 106.6316"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0230 - accuracy: 0.9717 - auc: 0.9505 - cross entropy: 0.0985 - fn: 30.5714 - fp: 2692.1978 - loss: 0.3364 - prc: 0.3086 - precision: 0.0454 - recall: 0.7986 - tn: 91290.4062 - tp: 127.3956 - val_Brier score: 0.0100 - val_accuracy: 0.9885 - val_auc: 0.9839 - val_cross entropy: 0.0538 - val_fn: 5.0000 - val_fp: 517.0000 - val_loss: 0.0538 - val_prc: 0.6362 - val_precision: 0.1296 - val_recall: 0.9390 - val_tn: 44970.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 53ms/step - Brier score: 0.0308 - accuracy: 0.9624 - auc: 0.7143 - cross entropy: 0.1212 - fn: 1.0000 - fp: 76.0000 - loss: 0.9833 - prc: 0.1025 - precision: 0.0256 - recall: 0.6667 - tn: 1969.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0275 - accuracy: 0.9659 - auc: 0.8561 - cross entropy: 0.1138 - fn: 9.0000 - fp: 936.6154 - loss: 0.5649 - prc: 0.2057 - precision: 0.0327 - recall: 0.7563 - tn: 26668.4609 - tp: 33.9231"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0273 - accuracy: 0.9660 - auc: 0.8907 - cross entropy: 0.1137 - fn: 15.8627 - fp: 1791.0000 - loss: 0.4747 - prc: 0.2438 - precision: 0.0362 - recall: 0.7906 - tn: 51369.2930 - tp: 71.8431"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0272 - accuracy: 0.9662 - auc: 0.9074 - cross entropy: 0.1137 - fn: 21.0519 - fp: 2667.7144 - loss: 0.4235 - prc: 0.2648 - precision: 0.0381 - recall: 0.8141 - tn: 77070.5078 - tp: 112.7273"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0271 - accuracy: 0.9663 - auc: 0.9128 - cross entropy: 0.1138 - fn: 24.7473 - fp: 3137.8132 - loss: 0.4094 - prc: 0.2688 - precision: 0.0387 - recall: 0.8191 - tn: 90844.3438 - tp: 133.6703 - val_Brier score: 0.0114 - val_accuracy: 0.9865 - val_auc: 0.9853 - val_cross entropy: 0.0596 - val_fn: 5.0000 - val_fp: 609.0000 - val_loss: 0.0596 - val_prc: 0.6135 - val_precision: 0.1122 - val_recall: 0.9390 - val_tn: 44878.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 10/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0274 - accuracy: 0.9673 - auc: 0.9987 - cross entropy: 0.1102 - fn: 0.0000e+00 - fp: 67.0000 - loss: 0.0559 - prc: 0.2606 - precision: 0.0290 - recall: 1.0000 - tn: 1979.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0286 - accuracy: 0.9647 - auc: 0.9891 - cross entropy: 0.1200 - fn: 5.1600 - fp: 937.9600 - loss: 0.1486 - prc: 0.3244 - precision: 0.0456 - recall: 0.9016 - tn: 25637.6406 - tp: 43.2400 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0286 - accuracy: 0.9646 - auc: 0.9788 - cross entropy: 0.1207 - fn: 11.4400 - fp: 1845.4600 - loss: 0.1910 - prc: 0.3107 - precision: 0.0433 - recall: 0.8863 - tn: 50286.9414 - tp: 80.1600"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m76/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0288 - accuracy: 0.9644 - auc: 0.9725 - cross entropy: 0.1214 - fn: 19.6053 - fp: 2802.9080 - loss: 0.2205 - prc: 0.3005 - precision: 0.0419 - recall: 0.8716 - tn: 75907.8672 - tp: 117.6184"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0289 - accuracy: 0.9642 - auc: 0.9704 - cross entropy: 0.1220 - fn: 24.0220 - fp: 3374.6594 - loss: 0.2304 - prc: 0.2944 - precision: 0.0412 - recall: 0.8665 - tn: 90603.2422 - tp: 138.6483 - val_Brier score: 0.0141 - val_accuracy: 0.9837 - val_auc: 0.9858 - val_cross entropy: 0.0697 - val_fn: 5.0000 - val_fp: 739.0000 - val_loss: 0.0697 - val_prc: 0.5984 - val_precision: 0.0944 - val_recall: 0.9390 - val_tn: 44748.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 11/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 51ms/step - Brier score: 0.0360 - accuracy: 0.9580 - auc: 0.9853 - cross entropy: 0.1456 - fn: 0.0000e+00 - fp: 86.0000 - loss: 0.0851 - prc: 0.0163 - precision: 0.0115 - recall: 1.0000 - tn: 1961.0000 - tp: 1.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m24/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0338 - accuracy: 0.9592 - auc: 0.9645 - cross entropy: 0.1434 - fn: 5.9583 - fp: 1025.7500 - loss: 0.2547 - prc: 0.2007 - precision: 0.0332 - recall: 0.8934 - tn: 24529.9590 - tp: 38.3333 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0331 - accuracy: 0.9599 - auc: 0.9594 - cross entropy: 0.1403 - fn: 11.5957 - fp: 1935.5106 - loss: 0.2681 - prc: 0.2203 - precision: 0.0343 - recall: 0.8767 - tn: 47133.2539 - tp: 71.6383"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m70/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0329 - accuracy: 0.9601 - auc: 0.9572 - cross entropy: 0.1395 - fn: 17.2143 - fp: 2863.3428 - loss: 0.2753 - prc: 0.2272 - precision: 0.0348 - recall: 0.8714 - tn: 69717.2031 - tp: 106.2429"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0328 - accuracy: 0.9600 - auc: 0.9554 - cross entropy: 0.1394 - fn: 23.0989 - fp: 3730.7913 - loss: 0.2830 - prc: 0.2281 - precision: 0.0347 - recall: 0.8658 - tn: 90250.4062 - tp: 136.2747 - val_Brier score: 0.0158 - val_accuracy: 0.9821 - val_auc: 0.9870 - val_cross entropy: 0.0765 - val_fn: 5.0000 - val_fp: 809.0000 - val_loss: 0.0765 - val_prc: 0.5793 - val_precision: 0.0869 - val_recall: 0.9390 - val_tn: 44678.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 12/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 52ms/step - Brier score: 0.0344 - accuracy: 0.9565 - auc: 0.9435 - cross entropy: 0.1376 - fn: 3.0000 - fp: 86.0000 - loss: 0.9305 - prc: 0.2908 - precision: 0.0652 - recall: 0.6667 - tn: 1953.0000 - tp: 6.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m26/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0338 - accuracy: 0.9575 - auc: 0.9487 - cross entropy: 0.1381 - fn: 8.5769 - fp: 1164.9615 - loss: 0.3849 - prc: 0.2529 - precision: 0.0385 - recall: 0.8158 - tn: 26432.4238 - tp: 42.0385"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m51/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0345 - accuracy: 0.9569 - auc: 0.9479 - cross entropy: 0.1435 - fn: 15.3333 - fp: 2299.3333 - loss: 0.3537 - prc: 0.2374 - precision: 0.0355 - recall: 0.8274 - tn: 50855.0195 - tp: 78.3137"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0348 - accuracy: 0.9565 - auc: 0.9480 - cross entropy: 0.1453 - fn: 22.1818 - fp: 3477.0000 - loss: 0.3395 - prc: 0.2345 - precision: 0.0343 - recall: 0.8328 - tn: 76256.0625 - tp: 116.7533"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0348 - accuracy: 0.9565 - auc: 0.9489 - cross entropy: 0.1457 - fn: 25.3846 - fp: 4104.4395 - loss: 0.3314 - prc: 0.2346 - precision: 0.0340 - recall: 0.8358 - tn: 89873.6172 - tp: 137.1319 - val_Brier score: 0.0170 - val_accuracy: 0.9804 - val_auc: 0.9875 - val_cross entropy: 0.0810 - val_fn: 5.0000 - val_fp: 888.0000 - val_loss: 0.0810 - val_prc: 0.5611 - val_precision: 0.0798 - val_recall: 0.9390 - val_tn: 44599.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 13/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 53ms/step - Brier score: 0.0387 - accuracy: 0.9536 - auc: 0.9988 - cross entropy: 0.1505 - fn: 0.0000e+00 - fp: 95.0000 - loss: 0.0754 - prc: 0.2857 - precision: 0.0206 - recall: 1.0000 - tn: 1951.0000 - tp: 2.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m25/90\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0341 - accuracy: 0.9576 - auc: 0.9640 - cross entropy: 0.1439 - fn: 3.7200 - fp: 1120.7200 - loss: 0.2125 - prc: 0.2716 - precision: 0.0311 - recall: 0.9142 - tn: 25461.5195 - tp: 38.0400 "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0341 - accuracy: 0.9578 - auc: 0.9675 - cross entropy: 0.1439 - fn: 7.8400 - fp: 2189.5000 - loss: 0.2122 - prc: 0.2669 - precision: 0.0334 - recall: 0.9120 - tn: 49947.2812 - tp: 79.3800"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m77/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - Brier score: 0.0341 - accuracy: 0.9579 - auc: 0.9685 - cross entropy: 0.1439 - fn: 13.8701 - fp: 3341.4805 - loss: 0.2150 - prc: 0.2599 - precision: 0.0338 - recall: 0.9032 - tn: 76396.7812 - tp: 119.8701"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0341 - accuracy: 0.9579 - auc: 0.9679 - cross entropy: 0.1440 - fn: 17.4615 - fp: 3938.6704 - loss: 0.2195 - prc: 0.2564 - precision: 0.0337 - recall: 0.8983 - tn: 90044.4609 - tp: 139.9780 - val_Brier score: 0.0166 - val_accuracy: 0.9808 - val_auc: 0.9879 - val_cross entropy: 0.0798 - val_fn: 5.0000 - val_fp: 868.0000 - val_loss: 0.0798 - val_prc: 0.5770 - val_precision: 0.0815 - val_recall: 0.9390 - val_tn: 44619.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 13: early stopping\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Restoring model weights from the end of the best epoch: 3.\n"
]
}
],
"source": [
"weighted_model = make_model()\n",
"weighted_model.load_weights(initial_weights)\n",
"\n",
"weighted_history = weighted_model.fit(\n",
" train_features,\n",
" train_labels,\n",
" batch_size=BATCH_SIZE,\n",
" epochs=EPOCHS,\n",
" callbacks=[early_stopping()],\n",
" validation_data=(val_features, val_labels),\n",
" # The class weights go here\n",
" class_weight=class_weight)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "R0ynYRO0G3Lx"
},
"source": [
"### Check training history"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:24.884492Z",
"iopub.status.busy": "2024-08-20T01:25:24.883988Z",
"iopub.status.idle": "2024-08-20T01:25:25.365786Z",
"shell.execute_reply": "2024-08-20T01:25:25.365067Z"
},
"id": "BBe9FMO5ucTC"
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_metrics(weighted_history)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "REy6WClTZIwQ"
},
"source": [
"### Evaluate metrics"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:25.370536Z",
"iopub.status.busy": "2024-08-20T01:25:25.369853Z",
"iopub.status.idle": "2024-08-20T01:25:26.019141Z",
"shell.execute_reply": "2024-08-20T01:25:26.018363Z"
},
"id": "nifqscPGw-5w"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m12s\u001b[0m 141ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m47/90\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/28\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 40ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m28/28\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m28/28\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step\n"
]
}
],
"source": [
"train_predictions_weighted = weighted_model.predict(train_features, batch_size=BATCH_SIZE)\n",
"test_predictions_weighted = weighted_model.predict(test_features, batch_size=BATCH_SIZE)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:26.022816Z",
"iopub.status.busy": "2024-08-20T01:25:26.022244Z",
"iopub.status.idle": "2024-08-20T01:25:27.072221Z",
"shell.execute_reply": "2024-08-20T01:25:27.071578Z"
},
"id": "owKL2vdMBJr6"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"loss : 0.014986301772296429\n",
"compile_metrics : 0.014986301772296429\n",
"\n",
"Legitimate Transactions Detected (True Negatives): 56817\n",
"Legitimate Transactions Incorrectly Detected (False Positives): 43\n",
"Fraudulent Transactions Missed (False Negatives): 18\n",
"Fraudulent Transactions Detected (True Positives): 84\n",
"Total Fraudulent Transactions: 102\n"
]
},
{
"data": {
"image/png": 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fXli2bJnWDe4FBQXC7NmzBScnJ6Fy5cpCnTp1nvmwhSd5eXkJXl5e4ven3eIiCI8eotC0aVNBqVQKjRo1En744YcSt7jExcUJffr0Eezt7QWlUinY29sLQ4YMEf79998Sx3jyYQt//PGH0L59e8HU1FSwsLAQevXq9dSHLTx5C03xAw4ef+hBaYoftvCkp/18AGg9Refu3bvCyJEjhRo1aghVqlQRfHx8hAsXLpR6a8qaNWuEevXqCcbGxqU+bKE0j49z/fp1wdLSUujVq1eJfv369RPMzc2Fy5cvP/N8/f39BQ8PDyEvL09sS05OFg4dOiTcvXtXePjwoRAfHy9kZmY+dYw7d+4IAQEBQvXq1QUzMzPBy8tLOH78eKmxP34b1N27d4Vhw4YJzs7OgpmZmaBSqYQmTZoI8+bNE/Lz80vsX1RUJMybN09wdHQUlEql0KRJE+GHH3545vkRlSeFIJRhlQURvbYyMjLg7u6Opk2bYtOmTeIK8McVFRVh+/bt8PPzM0CERK8uJlEiwr///gtfX19kZ2dj/Pjx6NKlC+zt7ZGdnY3Dhw9j+fLlUKvVOHHiRKm3QRHJFZMoEQF4tCJ24cKFWLt2rdYtK1WrVsXQoUMRGhqKWrVqGTBColcPkygRaREEAZcuXYJarYaFhQVcXFygVCoNHRbRK4lJlIiISE+8T5SIiEhPTKJERER6YhIlIiLS02v5xKKCDOle20X0LKb2HZ7fiUgChfn/STqelP9OVq5RT7KxKprXMokSEdFzaKR7Y5KcsZxLRESkJ85EiYjkSCj7u23p6ZhEiYjkSIcXxNPTsZxLRESkJ85EiYhkSGA5VxJMokREcsRyriRYziUiItITZ6JERHLEcq4kmESJiOSID1uQBMu5REREeuJMlIhIjljOlQSTKBGRHHF1riRYziUiItITZ6JERDLEhy1Ig0mUiEiOWM6VBMu5REREeuJMlIhIjljOlQSTKBGRHPFhC5JgOZeIiEhPnIkSEckRy7mSYBIlIpIjrs6VBMu5REREeuJMlIhIjljOlQSTKBGRHLGcKwmWc4mIiPTEmSgRkQwJAu8TlQKTKBGRHPGaqCRYziUiItITZ6JERHLEhUWSYBIlIpIjlnMlwXIuERGRnjgTJSKSI77FRRJMokREcsRyriRYziUiItITZ6JERHLE1bmSYBIlIpIjlnMlwXIuERGRnjgTJSKSI5ZzJcEkSkQkR0yikmA5l4iISE9MokREMiQIRZJ9dDFr1iwoFAqtT+PGjcXtubm5CAwMRPXq1VGlShUMGDAAqampWmOkpKTA19cXZmZmsLGxwZQpU1BYWKjVZ//+/WjVqhVUKhWcnZ0RGRlZIpYVK1agbt26MDExgYeHB44dO6bTuQBMokRE8qTRSPfRUZMmTXDr1i3xc/jwYXFbcHAwduzYga1bt+LAgQO4efMm+vfvL24vKiqCr68v8vPzceTIEaxfvx6RkZEIDQ0V+1y5cgW+vr7o3LkzEhMTMWnSJIwePRp79uwR+2zevBkhISGYOXMmTpw4gRYtWsDHxwdpaWk6nYtCEARB55/AK64g47KhQyCZMLXvYOgQSCYK8/+TdLyH+7+TbCzTTqPK3HfWrFmIiopCYmJiiW1ZWVmoWbMmNm7cCD8/PwDAhQsX4OLigvj4eLRr1w67d+9Gz549cfPmTdja2gIAVq1ahWnTpiE9PR1KpRLTpk1DdHQ0zpw5I449ePBgZGZmIiYmBgDg4eGBNm3aYPny5QAAjUaDOnXqICgoCNOnTy/z+XAmSkQkR4JGsk9eXh6ys7O1Pnl5eU899MWLF2Fvb4969eph6NChSElJAQAkJCSgoKAA3t7eYt/GjRvDwcEB8fHxAID4+Hg0a9ZMTKAA4OPjg+zsbJw9e1bs8/gYxX2Kx8jPz0dCQoJWHyMjI3h7e4t9yopJlIhIjiQs54aFhcHS0lLrExYWVuphPTw8EBkZiZiYGKxcuRJXrlxBhw4dcO/ePajVaiiVSlhZWWntY2trC7VaDQBQq9VaCbR4e/G2Z/XJzs7Gw4cPkZGRgaKiolL7FI9RVrzFhYiIXsiMGTMQEhKi1aZSqUrt2717d/HPzZs3h4eHBxwdHbFlyxaYmpqWa5zlgTNRIiI5krCcq1KpYGFhofV5WhJ9kpWVFRo2bIhLly7Bzs4O+fn5yMzM1OqTmpoKOzs7AICdnV2J1brF35/Xx8LCAqampqhRowaMjY1L7VM8RlkxiRIRyZEBV+c+7v79+0hOTkatWrXg7u6OypUrIy4uTtyelJSElJQUeHp6AgA8PT1x+vRprVW0sbGxsLCwgKurq9jn8TGK+xSPoVQq4e7urtVHo9EgLi5O7FNWTKJERPTSTJ48GQcOHMDVq1dx5MgR9OvXD8bGxhgyZAgsLS0REBCAkJAQ7Nu3DwkJCRg5ciQ8PT3Rrl07AEDXrl3h6uqK4cOH49SpU9izZw8+/fRTBAYGirPfsWPH4vLly5g6dSouXLiAiIgIbNmyBcHBwWIcISEhWLNmDdavX4/z589j3LhxyMnJwciRI3U6H14TJSKSIwO9xeXGjRsYMmQIbt++jZo1a+LNN9/E0aNHUbNmTQDA4sWLYWRkhAEDBiAvLw8+Pj6IiIgQ9zc2NsbOnTsxbtw4eHp6wtzcHP7+/pgzZ47Yx8nJCdHR0QgODsbSpUtRu3ZtrF27Fj4+PmKfQYMGIT09HaGhoVCr1XBzc0NMTEyJxUbPw/tEiV4A7xOll0Xy+0R3h0s2lmn3CZKNVdGwnEtERKQnlnOJiOSIb3GRBJMoEZEcGeia6OuG5VwiIiI9cSZKRCRHLOdKgkmUiEiOWM6VBMu5REREeuJMlIhIjljOlQSTKBGRHLGcKwmWc4mIiPTEmSgRkRyxnCsJJlEiIjliEpUEy7lERER64kyUiEiOXr8XeBkEkygRkRyxnCsJlnOJiIj0xJkoEZEccSYqCSZRIiI54sMWJMFyLhERkZ44EyUikiOWcyXBJEpEJEe8xUUSLOcSERHpiTNRIiI5YjlXEkyiRERyxCQqCZZziYiI9MSZKBGRHPE+UUkwiRIRyZCg4epcKbCcS0REpCfORImI5IgLiyTBJEpEJEe8JioJlnOJiIj0xJkoEZEccWGRJJhEiYjkiNdEJcFyLhERkZ44EyUikiPORCXBJEpEJEd8FZokWM4lIiLSE2eiRERyxHKuJJhEK6gV3/6Ald/9qNXm5FAbOzatEb8nnjmP8G/W4/S5CzAyMkLjBvXxzeIvYKJSAQCuptzAohXf4uTpcygoKEBDZycEjX4Pbd1biGPMW7wSiafP4eLlq6jn6ICf1694bhwAYGqiwvG4KAnPmCqyqVMCMW/ux1gavhYfTZ4JAIhY8SXefutN2Nvb4v79B4g/+jdmfDwXSUnJBo5WJniLiySYRCswZydHrF06T/xubGws/jnxzHmMDfkUo4cPwsfB42BsbIykS5dhpFCIfQKnzoJDbXt8Gz4fJiolNmyJQuDUmdi95TvUqG4t9uvn2xX/nEvCv5eulIhh5JABGNS3h1ZbwIQZaOrSUMpTpQqstXsLjBk9DKf+OafVfuLEP9i06RekXP8P1tWsEBr6EXZHb4Jzw3bQcJZEFQSTaAVmbGyslewet2DpNxjq1wejhw8U25wca4t/vpuZhWvX/8Oc6ZPQyNkJABA8diR++mUnLl6+Jo77cfA4AMCdzKxSk6iZmSnMzEzF7xcuXkby1RSETgl68ROkCs/c3Azff78cY8dNxcczJmhtW/vt/1Uwrl27gdCZC3Ay4Q/UrVsHly9fe9mhyg8f+ycJgybRjIwMfPfdd4iPj4darQYA2NnZ4X//+x9GjBiBmjVrGjK8V17Kjf/QufdQqFRKtGjSGJPGjkQtOxvcvpuJf84lwbdrZwz9IATX/7uFeo61MeF9f7Rq0RQAYGVpASeH2vgtJg4ujZyhrFwZW37dBetqVnBt5Kx3TL/siEHdOm/A3a2pVKdJFdiy8HnYvSsOcXsPlUiijzMzM8WI9wbh8uVruH795kuMUMZYzpWEwVbnHj9+HA0bNkR4eDgsLS3RsWNHdOzYEZaWlggPD0fjxo3x999/P3ecvLw8ZGdna33y8vJewhkYVnPXRvjik4+w6usv8Nnk8bhxKxXvfTgFOTkPcOO/WwCAiO9+hF/vbvjm68/h0tAZARNn4Nr1/wAACoUCa5bOw/l/k+HRpT/c3+qN73/ajm++/hyWFlX1iikvLx87f9+H/r18JDtPqrgGDuyNli2b4uNPw57aZ+wH/si88y+yMy/Bp1tndOsxBAUFBS8xSqIXY7CZaFBQEN555x2sWrUKiseu0wGAIAgYO3YsgoKCEB8f/8xxwsLCMHv2bK22T6dMQOjUiZLH/Crp4NlG/HMjZyc0c22ErgP8EbP3EOrVrQMAeKdPD/Tz7QoAcGnojKMJifhl5+8IHjcSgiBg7qIIVK9mifURC2GiUuHnHTEYP3UWflobjpo1Si8TP0vcwSN48OAhenf3luYkqcKqXdseixfNQbceQ575S+3GTb/gj7iDqGVng5CQsdi0cRU6evWVxS/ChibwurMkDJZET506hcjIyBIJFHg0SwoODkbLli2fO86MGTMQEhKi1WZ07z/J4qwoLKpWgWOdN5By4yY8/v/q2vpODlp96jk6QJ2aBgD4KyERB44cw5GYLahibg4AcG00HvHHT+LX3X9oXUstq593xKBj+7aoYV3tBc+GKrpWrZrB1rYmjv8VI7ZVqlQJHTq0Q+CHI2BWxQkajQbZ2feQnX0Ply5dwdG/TiAj7Rz69u2GzZt/NWD0MsFyriQMVs61s7PDsWPHnrr92LFjsLW1fe44KpUKFhYWWh/V/7+FQ04ePHiI6//dQs0a1nijli1salTH1Ws3tPpcu34Dtewe/Uxzcx/9pm+k0P4rYKRQ6LUy8sZNNY6d+Af9e7KUS8DevYfRouVbcG/TVfwc/zsRGzdth3ubrqX+HVMoFFAoFFAp5ff/X6q4DDYTnTx5Mt5//30kJCTg7bffFhNmamoq4uLisGbNGnz11VeGCu+Vt3D5GnRq7wF7O1ukZdzGirU/wNjYCD28vaBQKDDy3QFY8e0PaNTACY0b1Mevu/7AlWs38PUXnwAAWjR1gUXVKvj4i0UYO/JdmKiU2PZbDG7cSkXH/7UVj5Ny4yYePHiIjNt3kZeXhwv/PrqHr76TAypXriz2277zd9Ssbo0O7Vq/3B8EvZLu38/B2bNJWm0Pch7g9u27OHs2CU5ODhj4Tm/Exh5AesZt1H7DHlOnBuLhw1zsjokzUNQyw9W5kjBYEg0MDESNGjWwePFiREREoKioCMCj2zbc3d0RGRmJgQN1LynKRWpaBqbO/BKZ2dmwtrJEy+ZN8OM3i2FdzQoAMHxQP+TlF+DL8NXIzr6Hhs71sGbJXDjUtgcAVLOyxKpFnyN89XoETJiOwsJCODs5Ytn8UDRuUE88Tuj8Jfj75Gnxu9/I8QCAPdsi8UatR7/4aDQaRO2ORZ8e3lr3qhI9TW5uHt5s3xYTgkajWjVLpKZm4NDho+jg1Qfp6bcNHZ48sJwrCYUgGP4pxAUFBcjIyAAA1KhRQ2uGo9d4GZelCIvouUztOxg6BJKJwnxp13rkzBkq2VjmoSWfWiYXr8TDFipXroxatWoZOgwiIvng6lxJvBJJlIiIXjKWcyXBV6ERERHpiTNRIiI54upcSTCJEhHJEcu5kmA5l4iISE+ciRIRyRCfnSsNzkSJiIj0xCRKRCRHGkG6j57mz58PhUKBSZMmiW25ubkIDAxE9erVUaVKFQwYMACpqala+6WkpMDX1xdmZmawsbHBlClTUFhYqNVn//79aNWqFVQqFZydnREZGVni+CtWrEDdunVhYmICDw+PZz7P/WmYRImI5MjASfT48eP45ptv0Lx5c6324OBg7NixA1u3bsWBAwdw8+ZN9O/fX9xeVFQEX19f5Ofn48iRI1i/fj0iIyMRGhoq9rly5Qp8fX3RuXNnJCYmYtKkSRg9ejT27Nkj9tm8eTNCQkIwc+ZMnDhxAi1atICPjw/S0tJ0Oo9X4rF/UuNj/+hl4WP/6GWR+rF/96f0k2ysKgu363bs+/fRqlUrRERE4IsvvoCbmxuWLFmCrKws1KxZExs3boSfnx8A4MKFC3BxcUF8fDzatWuH3bt3o2fPnrh586b44pJVq1Zh2rRpSE9Ph1KpxLRp0xAdHY0zZ86Ixxw8eDAyMzMRE/Po9XweHh5o06YNli9fDuDRM8Dr1KmDoKAgTJ8+vcznwpkoEZEcCRrJPnl5ecjOztb6POvF6oGBgfD19YW3t7dWe0JCAgoKCrTaGzduDAcHB8THxwMA4uPj0axZM61XZfr4+CA7Oxtnz54V+zw5to+PjzhGfn4+EhIStPoYGRnB29tb7FNWTKJERHIkYTk3LCwMlpaWWp+wsLBSD/vTTz/hxIkTpW5Xq9VQKpWwsrLSare1tYVarRb7PPmu6eLvz+uTnZ2Nhw8fIiMjA0VFRaX2KR6jrHiLCxERvZAZM2YgJCREq02lKvly9evXr2PixImIjY2FiYnJywqvXDGJEhHJkCDhE4tUKlWpSfNJCQkJSEtLQ6tWrcS2oqIiHDx4EMuXL8eePXuQn5+PzMxMrdloamoq7OzsAAB2dnYlVtEWr959vM+TK3pTU1NhYWEBU1NTGBsbw9jYuNQ+xWOUFcu5RERyZIDVuW+//TZOnz6NxMRE8dO6dWsMHTpU/HPlypURFxcn7pOUlISUlBR4enoCADw9PXH69GmtVbSxsbGwsLCAq6ur2OfxMYr7FI+hVCrh7u6u1Uej0SAuLk7sU1aciRIR0UtRtWpVNG3aVKvN3Nwc1atXF9sDAgIQEhICa2trWFhYICgoCJ6enmjXrh0AoGvXrnB1dcXw4cOxYMECqNVqfPrppwgMDBRnw2PHjsXy5csxdepUjBo1Cnv37sWWLVsQHR0tHjckJAT+/v5o3bo12rZtiyVLliAnJwcjR47U6ZyYRImI5OgVfezf4sWLYWRkhAEDBiAvLw8+Pj6IiIgQtxsbG2Pnzp0YN24cPD09YW5uDn9/f8yZM0fs4+TkhOjoaAQHB2Pp0qWoXbs21q5dCx8fH7HPoEGDkJ6ejtDQUKjVari5uSEmJqbEYqPn4X2iRC+A94nSyyL1faL3Puwu2VhVI3ZLNlZFw2uiREREemI5l4hIjvg+UUkwiRIRydBreCXPIFjOJSIi0hNnokREcsRyriSYRImI5IhJVBIs5xIREemJM1EiIhmS8tm5csYkSkQkR0yikmA5l4iISE+ciRIRydGr+ejcCodJlIhIhnhNVBos5xIREemJM1EiIjniTFQSTKJERHLEa6KSYDmXiIhIT5yJEhHJEBcWSYNJlIhIjljOlQTLuURERHriTJSISIZYzpUGkygRkRyxnCsJlnOJiIj0xJkoEZEMCZyJSoJJlIhIjphEJcFyLhERkZ44EyUikiGWc6XBJEpEJEdMopJgOZeIiEhPnIkSEckQy7nSYBIlIpIhJlFpsJxLRESkJ85EiYhkiDNRaTCJEhHJkaAwdASvhTIl0fDw8DIPOGHCBL2DISIiqkjKlEQXL15cpsEUCgWTKBFRBcByrjTKlESvXLlS3nEQEdFLJGhYzpWC3qtz8/PzkZSUhMLCQinjISIiqjB0TqIPHjxAQEAAzMzM0KRJE6SkpAAAgoKCMH/+fMkDJCIi6Qka6T5ypnMSnTFjBk6dOoX9+/fDxMREbPf29sbmzZslDY6IiMqHICgk+8iZzre4REVFYfPmzWjXrh0Uiv/74TVp0gTJycmSBkdERPQq0zmJpqenw8bGpkR7Tk6OVlIlIqJXl9zLsFLRuZzbunVrREdHi9+LE+fatWvh6ekpXWRERFRuBI1Cso+c6TwTnTdvHrp3745z586hsLAQS5cuxblz53DkyBEcOHCgPGIkIiJ6Jek8E33zzTeRmJiIwsJCNGvWDL///jtsbGwQHx8Pd3f38oiRiIgkJgjSfeRMr2fn1q9fH2vWrJE6FiIieknkXoaVil5JtKioCNu3b8f58+cBAK6urujTpw8qVeLz7ImISD50znpnz55F7969oVar0ahRIwDAl19+iZo1a2LHjh1o2rSp5EESEZG0OBOVhs7XREePHo0mTZrgxo0bOHHiBE6cOIHr16+jefPmeP/998sjRiIikhiviUpD55loYmIi/v77b1SrVk1sq1atGubOnYs2bdpIGhwREdGrTOeZaMOGDZGamlqiPS0tDc7OzpIERURE5Yv3iUqjTDPR7Oxs8c9hYWGYMGECZs2ahXbt2gEAjh49ijlz5uDLL78snyiJiEhScn/mrVQUgvD8iraRkZHWI/2Kdylue/x7UVFRecSpk4KMy4YOgWTC1L6DoUMgmSjM/0/S8ZKb+kg2Vv0zeyQbq6Ip00x037595R0HERG9RHx2rjTKlES9vLzKOw4iInqJNCznSkLvpyM8ePAAKSkpyM/P12pv3rz5CwdFRERUEej1KrSRI0di9+7dpW5/Fa6JEhHRs3FhkTR0vsVl0qRJyMzMxF9//QVTU1PExMRg/fr1aNCgAX777bfyiJGIiCTGW1ykoXMS3bt3L77++mu0bt0aRkZGcHR0xLBhw7BgwQKEhYWVR4xERPSaWLlyJZo3bw4LCwtYWFjA09NTq7KZm5uLwMBAVK9eHVWqVMGAAQNKPJsgJSUFvr6+MDMzg42NDaZMmYLCwkKtPvv370erVq2gUqng7OyMyMjIErGsWLECdevWhYmJCTw8PHDs2DGdz0fnJJqTkwMbGxsAj55UlJ6eDgBo1qwZTpw4oXMARET08hnqsX+1a9fG/PnzkZCQgL///htvvfUW+vTpg7NnzwIAgoODsWPHDmzduhUHDhzAzZs30b9/f3H/oqIi+Pr6Ij8/H0eOHMH69esRGRmJ0NBQsc+VK1fg6+uLzp07IzExEZMmTcLo0aOxZ8//3YqzefNmhISEYObMmThx4gRatGgBHx8fpKWl6XQ+ZbpP9HFt2rTBF198AR8fH/Tu3RtWVlYICwtDeHg4tm3bhuTkZJ0CKA+8T5ReFt4nSi+L1PeJnqvvK9lY9c/9gry8PK02lUoFlUpVpv2tra2xcOFC+Pn5oWbNmti4cSP8/PwAABcuXICLiwvi4+PRrl077N69Gz179sTNmzdha2sLAFi1ahWmTZuG9PR0KJVKTJs2DdHR0Thz5ox4jMGDByMzMxMxMTEAAA8PD7Rp0wbLly8HAGg0GtSpUwdBQUGYPn16mc9d55noxIkTcevWLQDAzJkzsXv3bjg4OCA8PBzz5s3TdTgiIqrgwsLCYGlpqfUpy+W9oqIi/PTTT8jJyYGnpycSEhJQUFAAb29vsU/jxo3h4OCA+Ph4AEB8fDyaNWsmJlAA8PHxQXZ2tjibjY+P1xqjuE/xGPn5+UhISNDqY2RkBG9vb7FPWem8OnfYsGHin93d3XHt2jVcuHABDg4OqFGjhq7DERGRAUh5n+iMGTMQEhKi1fasWejp06fh6emJ3NxcVKlSBdu3b4erqysSExOhVCphZWWl1d/W1hZqtRoAoFartRJo8fbibc/qk52djYcPH+Lu3bsoKioqtc+FCxfKfuJ4gftEi5mZmaFVq1YvOgwREb1EUt7iokvpFgAaNWqExMREZGVlYdu2bfD398eBAwcki+dlKlMSffI3jGf5+uuv9Q6GiIhef0qlUnzrl7u7O44fP46lS5di0KBByM/PR2ZmptZsNDU1FXZ2dgAAOzu7Eqtoi1fvPt7nyRW9qampsLCwgKmpKYyNjWFsbFxqn+IxyqpMSfTkyZNlGuzxh9QTEdGr61V6mbZGo0FeXh7c3d1RuXJlxMXFYcCAAQCApKQkpKSkwNPTEwDg6emJuXPnIi0tTbxTJDY2FhYWFnB1dRX77Nq1S+sYsbGx4hhKpRLu7u6Ii4tD3759xRji4uIwfvx4nWLnA+iJiGTIUM/OnTFjBrp37w4HBwfcu3cPGzduxP79+7Fnzx5YWloiICAAISEhsLa2hoWFBYKCguDp6Sm+erNr165wdXXF8OHDsWDBAqjVanz66acIDAwUS8pjx47F8uXLMXXqVIwaNQp79+7Fli1bEB0dLcYREhICf39/tG7dGm3btsWSJUuQk5ODkSNH6nQ+L3xNlIiIqKzS0tLw3nvv4datW7C0tETz5s2xZ88edOnSBQCwePFiGBkZYcCAAcjLy4OPjw8iIiLE/Y2NjbFz506MGzcOnp6eMDc3h7+/P+bMmSP2cXJyQnR0NIKDg7F06VLUrl0ba9euhY/P/73+bdCgQUhPT0doaCjUajXc3NwQExNTYrHR8+h8n2hFwPtE6WXhfaL0skh9n+hJhz6SjdUy5VfJxqpoOBMlIpKh12/6ZBg6P2yBiIiIHuFMlIhIhvhSbmmUKYnq8oqz3r176x2MVHidiojo2fg+UWmUKYkW30fzPAqFgi/lJiIi2ShTEtVoNOUdBxERvUQs50qD10SJiGSIi3OloVcSzcnJwYEDB5CSkoL8/HytbRMmTJAkMCIioledzkn05MmT6NGjBx48eICcnBxYW1sjIyMDZmZmsLGxYRIlIqoAWM6Vhs73iQYHB6NXr164e/cuTE1NcfToUVy7dg3u7u746quvyiNGIiKSmCAoJPvImc5JNDExER999BGMjIxgbGyMvLw81KlTBwsWLMDHH39cHjESERG9knROopUrV4aR0aPdbGxskJKSAgCwtLTE9evXpY2OiIjKhUbCj5zpfE20ZcuWOH78OBo0aAAvLy+EhoYiIyMDGzZsQNOmTcsjRiIikpgAeZdhpaLzTHTevHmoVasWAGDu3LmoVq0axo0bh/T0dKxevVryAImIiF5Vr+Wr0Cop3zB0CEREkpL6VWj7bd+RbKxOqVslG6ui4cMWiIhkSMNyriR0TqJOTk5QKJ7+w798mS/EJiIiedA5iU6aNEnre0FBAU6ePImYmBhMmTJFqriIiKgccWGRNHROohMnTiy1fcWKFfj7779fOCAiIip/cr81RSo6r859mu7du+Pnn3+WajgiIqJXnmQLi7Zt2wZra2uphiMionLEcq409HrYwuMLiwRBgFqtRnp6OiIiIiQNjoiIygfLudLQOYn26dNHK4kaGRmhZs2a6NSpExo3bixpcERERK8ynZPorFmzyiEMIiJ6mTgTlYbOC4uMjY2RlpZWov327dswNjaWJCgiIipfAhSSfeRM5yT6tKcE5uXlQalUvnBAREREFUWZy7nh4eEAAIVCgbVr16JKlSritqKiIhw8eJDXRImIKgiNvCeQkilzEl28eDGARzPRVatWaZVulUol6tati1WrVkkfIRERSY7PzpVGmZPolStXAACdO3fGL7/8gmrVqpVbUERERBWBzqtz9+3bVx5xEBHRS/TavQPTQHReWDRgwAB8+eWXJdoXLFiAd96R7v10RERUfjQSfuRM5yR68OBB9OjRo0R79+7dcfDgQUmCIiIiqgh0Lufev3+/1FtZKleujOzsbEmCIiKi8qV5xnuhqex0nok2a9YMmzdvLtH+008/wdXVVZKgiIiofAkSfuRM55noZ599hv79+yM5ORlvvfUWACAuLg6bNm3C1q1bJQ+QiIjoVaVzEu3VqxeioqIwb948bNu2DaampmjevDn++OMPeHl5lUeMREQkMbkvCJKKXu8T9fX1ha+vb4n2M2fOoGnTpi8cFBERlS8+sUgaOl8TfdK9e/ewevVqtG3bFi1atJAiJiIiogpB7yR68OBBvPfee6hVqxa++uorvPXWWzh69KiUsRERUTnRQCHZR850Kueq1WpERkbi22+/RXZ2NgYOHIi8vDxERUVxZS4RUQUi91W1UinzTLRXr15o1KgR/vnnHyxZsgQ3b97EsmXLyjM2IiKiV1qZZ6K7d+/GhAkTMG7cODRo0KA8YyIionLGhUXSKPNM9PDhw7h37x7c3d3h4eGB5cuXIyMjozxjIyKicsJn50qjzEm0Xbt2WLNmDW7duoUPPvgAP/30E+zt7aHRaBAbG4t79+6VZ5xERESvHJ1X55qbm2PUqFE4fPgwTp8+jY8++gjz58+HjY0NevfuXR4xEhGRxPjYP2m80H2ijRo1woIFC3Djxg1s2rRJqpiIiKicaRTSfeTshR+2AADGxsbo27cvfvvtNymGIyIiqhD0euwfERFVbHJfECQVJlEiIhliEpWGJOVcIiIiOeJMlIhIhgSZLwiSCpMoEZEMsZwrDZZziYiI9MSZKBGRDHEmKg0mUSIiGZL7k4akwnIuERGRnphEiYhkyFCP/QsLC0ObNm1QtWpV2NjYoG/fvkhKStLqk5ubi8DAQFSvXh1VqlTBgAEDkJqaqtUnJSUFvr6+MDMzg42NDaZMmYLCwkKtPvv370erVq2gUqng7OyMyMjIEvGsWLECdevWhYmJCTw8PHDs2DGdzodJlIhIhgz1KrQDBw4gMDAQR48eRWxsLAoKCtC1a1fk5OSIfYKDg7Fjxw5s3boVBw4cwM2bN9G/f39xe1FREXx9fZGfn48jR45g/fr1iIyMRGhoqNjnypUr8PX1RefOnZGYmIhJkyZh9OjR2LNnj9hn8+bNCAkJwcyZM3HixAm0aNECPj4+SEtLK/P5KARBeO1K45WUbxg6BCIiSRXm/yfpeIsdhkk2VnDKD3rvm56eDhsbGxw4cAAdO3ZEVlYWatasiY0bN8LPzw8AcOHCBbi4uCA+Ph7t2rXD7t270bNnT9y8eRO2trYAgFWrVmHatGlIT0+HUqnEtGnTEB0djTNnzojHGjx4MDIzMxETEwMA8PDwQJs2bbB8+XIAgEajQZ06dRAUFITp06eXKX7ORImIZEjKmWheXh6ys7O1Pnl5eWWKIysrCwBgbW0NAEhISEBBQQG8vb3FPo0bN4aDgwPi4+MBAPHx8WjWrJmYQAHAx8cH2dnZOHv2rNjn8TGK+xSPkZ+fj4SEBK0+RkZG8Pb2FvuUBZMoEZEMSfk+0bCwMFhaWmp9wsLCnhuDRqPBpEmT0L59ezRt2hQAoFaroVQqYWVlpdXX1tYWarVa7PN4Ai3eXrztWX2ys7Px8OFDZGRkoKioqNQ+xWOUBW9xISKiFzJjxgyEhIRotalUqufuFxgYiDNnzuDw4cPlFVq5YxIlIpIhKV+mrVKpypQ0Hzd+/Hjs3LkTBw8eRO3atcV2Ozs75OfnIzMzU2s2mpqaCjs7O7HPk6toi1fvPt7nyRW9qampsLCwgKmpKYyNjWFsbFxqn+IxyoLlXCIiGTLU6lxBEDB+/Hhs374de/fuhZOTk9Z2d3d3VK5cGXFxcWJbUlISUlJS4OnpCQDw9PTE6dOntVbRxsbGwsLCAq6urmKfx8co7lM8hlKphLu7u1YfjUaDuLg4sU9ZcCZKREQvTWBgIDZu3Ihff/0VVatWFa8/WlpawtTUFJaWlggICEBISAisra1hYWGBoKAgeHp6ol27dgCArl27wtXVFcOHD8eCBQugVqvx6aefIjAwUJwRjx07FsuXL8fUqVMxatQo7N27F1u2bEF0dLQYS0hICPz9/dG6dWu0bdsWS5YsQU5ODkaOHFnm82ESJSKSIUPd27hy5UoAQKdOnbTa161bhxEjRgAAFi9eDCMjIwwYMAB5eXnw8fFBRESE2NfY2Bg7d+7EuHHj4OnpCXNzc/j7+2POnDliHycnJ0RHRyM4OBhLly5F7dq1sXbtWvj4+Ih9Bg0ahPT0dISGhkKtVsPNzQ0xMTElFhs9C+8TJSKqAKS+T3Su41DJxvrk2o+SjVXR8JooERGRnljOJSKSIb4KTRpMokREMvTaXcczEJZziYiI9MSZKBGRDLGcKw0mUSIiGZLyiUVyxnIuERGRnjgTJSKSIQ2XFkmCSZSISIaYQqXBci4REZGeOBMlIpIhrs6VBpMoEZEM8ZqoNFjOJSIi0hNnokREMsR5qDSYRImIZIjXRKXBci4REZGeOBMlIpIhLiySBpMoEZEMMYVKg+VcIiIiPXEmSkQkQ1xYJA0mUSIiGRJY0JUEy7lERER64kyUiEiGWM6VBpMoEZEM8RYXabCcS0REpCfORImIZIjzUGkwiRIRyRDLudJgOVdGOrzpgajtkUi5moDC/P/Qu7eP1nZzczMsXfIFrl7+G/eyLuGfU/vw/pjhBoqWKjIjIyPMnjUFF5PicS/rEpLO/4lPPp701P4rls9HYf5/mBA0+uUFSSQBzkRlxNzcDP/8cw7rIn/Cz1u/LbH9q4Uz0blTe/iPCMLVa9fRxdsLy5fNw81bauzcGWuAiKmimjolEB+8/x5GBUzC2XNJcHdvgW/XfI2srGwsX/GdVt8+fbrBw6MV/vvvloGilSeuzpUGk6iMxOzZh5g9+5663dOzNTb8sA0HDsYDANZ++yPGjBmGtm1aMomSTjzbtcZvO/Zg1+44AMC1azcweFAftGnjptXP3t4OSxd/gR4938VvUd8bIFL54sMWpMFyLoni4/9Gz55dYG9vBwDo5PU/NGxQD7GxBwwcGVU08Uf/xlud30SDBvUAAM2bu6L9/9pq/RKnUCiwfl04Fn29EufO/WuoUIleSIWfiebl5SEvL0+rTRAEKBQKA0VUcU2c9BlWrVyAlKsJKCgogEajwQfjpuLQ4b8MHRpVMF8uWA4Liyo4e/oAioqKYGxsjM9Cv8SmTdvFPlOnBKKwsBDLlpe8tEDlj+VcabzSM9Hr169j1KhRz+wTFhYGS0tLrY+gufeSIny9jA8cCQ+PVujbbwTatuuOKVPnYNnSuXj7rQ6GDo0qmHfe6YUhg/tj2HuBaOPRDSMDJiEkeCyGD38HANCqZTMEjQ/AqNHBBo5UvgQJ/ydnCkEQXtmfwKlTp9CqVSsUFRU9tU9pM9Fq1RtzJvochfn/ob/fKPz22x4AgImJCe5knIffO6PF61gA8M2qhaj9Ri349hpmqFCpArqSfBwLFi7HylXrxbaPZ0zEu+/2R9NmXpgQNBpfLZwJjeb/5kOVKlVCUVERrl+/CeeG7QwR9iutMP8/SccbWXeAZGOtu/qzZGNVNAYt5/7222/P3H758uXnjqFSqaBSqbTamEB1V7lyJSiVSq1/1ACgqEgDI6NXumBBryAzM1NoNNq/nxcVFYl/l3748WfE7T2ktX3Xzh/x48afEbl+y0uLU85YzpWGQZNo3759oVAo8KzJMBOidMzNzeDs7CR+d6rrgBYtmuDOnbu4fv0mDhw4gvnzP8XDh7m4lnIDHTt4YviwAZg8ZY4Bo6aKaGd0LGZMn4Dr1//D2XNJcHNrikkT30fk+p8AAHfu3MWdO3e19ikoKIRanY5//002RMiyo3l1i5AVikGTaK1atRAREYE+ffqUuj0xMRHu7u4vOarXV2v3Foj7Y5v4fdFXswAA67/fgoDRwXh32IeY+8UMfL9+GaytrXAt5T98FroA36zmrQekm4mTPsXsWVOxLHwebGyq4+bNVKxZ+wM+/2KxoUMjkpRBr4n27t0bbm5umDOn9JnOqVOn0LJlyxIlxueppHxDivCIiF4ZUl8THebYX7Kxfrj2i2RjVTQGnYlOmTIFOTk5T93u7OyMffue/nAAIiLSD5+dKw2DJtEOHZ5964S5uTm8vLxeUjRERES6qfAPWyAiIt3J/f5OqTCJEhHJEG9xkQZvACQiItITZ6JERDLEhUXS4EyUiIhIT5yJEhHJEBcWSYNJlIhIhriwSBos5xIREemJM1EiIhl6hd+CWaEwiRIRyRBX50qD5VwiIiI9cSZKRCRDXFgkDSZRIiIZ4i0u0mA5l4iISE+ciRIRyRAXFkmDSZSISIZ4i4s0WM4lIiLSE5MoEZEMaST86OLgwYPo1asX7O3toVAoEBUVpbVdEASEhoaiVq1aMDU1hbe3Ny5evKjV586dOxg6dCgsLCxgZWWFgIAA3L9/X6vPP//8gw4dOsDExAR16tTBggULSsSydetWNG7cGCYmJmjWrBl27dql49kwiRIRyZIg4f90kZOTgxYtWmDFihWlbl+wYAHCw8OxatUq/PXXXzA3N4ePjw9yc3PFPkOHDsXZs2cRGxuLnTt34uDBg3j//ffF7dnZ2ejatSscHR2RkJCAhQsXYtasWVi9erXY58iRIxgyZAgCAgJw8uRJ9O3bF3379sWZM2d0Oh+F8BoWxisp3zB0CEREkirM/0/S8brW6SbZWL9fj9FrP4VCge3bt6Nv374AHs1C7e3t8dFHH2Hy5MkAgKysLNja2iIyMhKDBw/G+fPn4erqiuPHj6N169YAgJiYGPTo0QM3btyAvb09Vq5ciU8++QRqtRpKpRIAMH36dERFReHChQsAgEGDBiEnJwc7d+4U42nXrh3c3NywatWqMp8DZ6JERDKkgSDZJy8vD9nZ2VqfvLw8nWO6cuUK1Go1vL29xTZLS0t4eHggPj4eABAfHw8rKysxgQKAt7c3jIyM8Ndff4l9OnbsKCZQAPDx8UFSUhLu3r0r9nn8OMV9io9TVkyiREQyJAiCZJ+wsDBYWlpqfcLCwnSOSa1WAwBsbW212m1tbcVtarUaNjY2WtsrVaoEa2trrT6ljfH4MZ7Wp3h7WfEWFyIieiEzZsxASEiIVptKpTJQNC8XkygRkQxJ+bAFlUolSdK0s7MDAKSmpqJWrVpie2pqKtzc3MQ+aWlpWvsVFhbizp074v52dnZITU3V6lP8/Xl9ireXFcu5REQyZKjVuc/i5OQEOzs7xMXFiW3Z2dn466+/4OnpCQDw9PREZmYmEhISxD579+6FRqOBh4eH2OfgwYMoKCgQ+8TGxqJRo0aoVq2a2Ofx4xT3KT5OWTGJEhHRS3P//n0kJiYiMTERwKPFRImJiUhJSYFCocCkSZPwxRdf4LfffsPp06fx3nvvwd7eXlzB6+Ligm7dumHMmDE4duwY/vzzT4wfPx6DBw+Gvb09AODdd9+FUqlEQEAAzp49i82bN2Pp0qVaJeeJEyciJiYGixYtwoULFzBr1iz8/fffGD9+vE7nw1tciIgqAKlvcen4xtuSjXXwv7jnd/r/9u/fj86dO5do9/f3R2RkJARBwMyZM7F69WpkZmbizTffREREBBo2bCj2vXPnDsaPH48dO3bAyMgIAwYMQHh4OKpUqSL2+eeffxAYGIjjx4+jRo0aCAoKwrRp07SOuXXrVnz66ae4evUqGjRogAULFqBHjx46nTuTKBFRBSB1Eu0gYRI9pEMSfd2wnEtERKQnrs4lIpIhvgpNGkyiREQyxCQqDZZziYiI9MSZKBGRDL2Ga0oNgkmUiEiGWM6VBsu5REREeuJMlIhIhqR8XJ+cMYkSEckQr4lKg+VcIiIiPXEmSkQkQ1xYJA0mUSIiGWI5Vxos5xIREemJM1EiIhliOVcaTKJERDLEW1ykwXIuERGRnjgTJSKSIQ0XFkmCSZSISIZYzpUGy7lERER64kyUiEiGWM6VBpMoEZEMsZwrDZZziYiI9MSZKBGRDLGcKw0mUSIiGWI5Vxos5xIREemJM1EiIhliOVcaTKJERDLEcq40WM4lIiLSE2eiREQyJAgaQ4fwWmASJSKSIb5PVBos5xIREemJM1EiIhkSuDpXEkyiREQyxHKuNFjOJSIi0hNnokREMsRyrjSYRImIZIhPLJIGy7lERER64kyUiEiG+Ng/aTCJEhHJEK+JSoPlXCIiIj1xJkpEJEO8T1QaTKJERDLEcq40WM4lIiLSE2eiREQyxPtEpcEkSkQkQyznSoPlXCIiIj1xJkpEJENcnSsNJlEiIhliOVcaLOcSERHpiTNRIiIZ4upcaTCJEhHJEB9ALw2Wc4mIiPTEmSgRkQyxnCsNJlEiIhni6lxpsJxLRESkJ85EiYhkiAuLpMEkSkQkQyznSoPlXCIiIj1xJkpEJEOciUqDSZSISIaYQqXBci4REZGeFALn9AQgLy8PYWFhmDFjBlQqlaHDodcY/67R64RJlAAA2dnZsLS0RFZWFiwsLAwdDr3G+HeNXics5xIREemJSZSIiEhPTKJERER6YhIlAIBKpcLMmTO50IPKHf+u0euEC4uIiIj0xJkoERGRnphEiYiI9MQkSkREpCcmUSIiIj0xiRJWrFiBunXrwsTEBB4eHjh27JihQ6LX0MGDB9GrVy/Y29tDoVAgKirK0CERvTAmUZnbvHkzQkJCMHPmTJw4cQItWrSAj48P0tLSDB0avWZycnLQokULrFixwtChEEmGt7jInIeHB9q0aYPly5cDADQaDerUqYOgoCBMnz7dwNHR60qhUGD79u3o27evoUMheiGcicpYfn4+EhIS4O3tLbYZGRnB29sb8fHxBoyMiKhiYBKVsYyMDBQVFcHW1lar3dbWFmq12kBRERFVHEyiREREemISlbEaNWrA2NgYqampWu2pqamws7MzUFRERBUHk6iMKZVKuLu7Iy4uTmzTaDSIi4uDp6enASMjIqoYKhk6ADKskJAQ+Pv7o3Xr1mjbti2WLFmCnJwcjBw50tCh0Wvm/v37uHTpkvj9ypUrSExMhLW1NRwcHAwYGZH+eIsLYfny5Vi4cCHUajXc3NwQHh4ODw8PQ4dFr5n9+/ejc+fOJdr9/f0RGRn58gMikgCTKBERkZ54TZSIiEhPTKJERER6YhIlIiLSE5MoERGRnphEiYiI9MQkSkREpCcmUSIiIj0xiRIREemJSZReeyNGjNB6+XOnTp0wadKklx7H/v37oVAokJmZ+dQ+CoUCUVFRZR5z1qxZcHNze6G4rl69CoVCgcTExBcah0iOmETJIEaMGAGFQgGFQgGlUglnZ2fMmTMHhYWF5X7sX375BZ9//nmZ+pYl8RGRfPEB9GQw3bp1w7p165CXl4ddu3YhMDAQlStXxowZM0r0zc/Ph1KplOS41tbWkoxDRMSZKBmMSqWCnZ0dHB0dMW7cOHh7e+O3334D8H8l2Llz58Le3h6NGjUCAFy/fh0DBw6ElZUVrK2t0adPH1y9elUcs6ioCCEhIbCyskL16tUxdepUPPl46CfLuXl5eZg2bRrq1KkDlUoFZ2dnfPvtt7h69ar4wPRq1apBoVBgxIgRAB69Mi4sLAxOTk4wNTVFixYtsG3bNq3j7Nq1Cw0bNoSpqSk6d+6sFWdZTZs2DQ0bNoSZmRnq1auHzz77DAUFBSX6ffPNN6hTpw7MzMwwcOBAZGVlaW1fu3YtXFxcYGJigsaNGyMiIkLnWIioJCZRemWYmpoiPz9f/B4XF4ekpCTExsZi586dKCgogI+PD6pWrYpDhw7hzz//RJUqVdCtWzdxv0WLFiEyMhLfffcdDh8+jDt37mD79u3PPO57772HTZs2ITw8HOfPn8c333yDKlWqoE6dOvj5558BAElJSbh16xaWLl0KAAgLC8P333+PVatW4ezZswgODsawYcNw4MABAI+Sff/+/dGrVy8kJiZi9OjRmD59us4/k6pVqyIyMhLnzp3D0qVLsWbNGixevFirz6VLl7Blyxbs2LEDMTExOHnyJD788ENx+48//ojQ0FDMnTsX58+fx7x58/DZZ59h/fr1OsdDRE8QiAzA399f6NOnjyAIgqDRaITY2FhBpVIJkydPFrfb2toKeXl54j4bNmwQGjVqJGg0GrEtLy9PMDU1Ffbs2SMIgiDUqlVLWLBggbi9oKBAqF27tngsQRAELy8vYeLEiYIgCEJSUpIAQIiNjS01zn379gkAhLt374ptubm5gpmZmXDkyBGtvgEBAcKQIUMEQRCEGTNmCK6urlrbp02bVmKsJwEQtm/f/tTtCxcuFNzd3cXvM2fOFIyNjYUbN26Ibbt37xaMjIyEW7duCYIgCPXr1xc2btyoNc7nn38ueHp6CoIgCFeuXBEACCdPnnzqcYmodLwmSgazc+dOVKlSBQUFBdBoNHj33Xcxa9YscXuzZs20roOeOnUKly5dQtWqVbXGyc3NRXJyMrKysnDr1i2td6FWqlQJrVu3LlHSLZaYmAhjY2N4eXmVOe5Lly7hwYMH6NKli1Z7fn4+WrZsCQA4f/58iXeyenp6lvkYxTZv3ozw8HAkJyfj/v37KCwshIWFhVYfBwcHvPHGG1rH0Wg0SEpKQtWqVZGcnIyAgACMGTNG7FNYWAhLS0ud4yEibUyiZDCdO3fGypUroVQqYW9vj0qVtP86mpuba32/f/8+3N3d8eOPP5YYq2bNmnrFYGpqqvM+9+/fBwBER0drJS/g0XVeqcTHx2Po0KGYPXs2fHx8YGlpiZ9++gmLFi3SOdY1a9aUSOrGxsaSxUokV0yiZDDm5uZwdnYuc/9WrVph8+bNsLGxKTEbK1arVi389ddf6NixI4BHM66EhAS0atWq1P7NmjWDRqPBgQMH4O3tXWJ78Uy4qKhIbHN1dYVKpUJKSspTZ7AuLi7iIqliR48eff5JPubIkSNwdHTEJ598IrZdu3atRL+UlBTcvHkT9vb24nGMjIzQqFEj2Nrawt7eHpcvX8bQoUN1Oj4RPR8XFlGFMXToUNSoUQN9+vTBoUOHcOXKFezfvx8TJkzAjRs3AAATJ07E/PnzERUVhQsXLuDDDz985j2edevWhb+/P0aNGoWoqChxzC1btgAAHB0doVAosHPnTqSnp+P+/fuoWrUqJk+ejODgYKxfvx7Jyck4ceIEli1bJi7WGTt2LC5evIgpU6YgKSkJGzduRGRkpE7n26BBA6SkpOCnn35CcnIywsPDS10kZWJiAn9/f5w6dQqHDh3ChAkTMHDgQNjZ2QEAZs+ejbCwMISHh+Pff//F6dOnsW7dOnz99dc6xUNEJTGJUoVhZmaGgwcPwsHBAf3794eLiwsCAgKQm5srzkw/+ugjDB8+HP7+/vD09ETVqlXRr1+/Z467cuVK+Pn54cMPP0Tjxo0xZswY5OTkAADeeOMNzJ49G9OnT4etrS3Gjx8PAPj888/x2WefISwsDC4uLujWrRuio6Ph5OQE4NF1yp9//hlRUVFo0aIFVq1ahXnz5ul0vr1790ZwcDDGjx8PNzc3HDlyBJ999lmJfs7Ozujfvz969OiBrl27onnz5lq3sIwePRpr167FunXr0KxZM3h5eSEyMlKMlYj0pxCetuKCiIiInokzUSIiIj0xiRIREemJSZSIiEhPTKJERER6YhIlIiLSE5MoERGRnphEiYiI9MQkSkREpCcmUSIiIj0xiRIREemJSZSIiEhP/w88yhzIWkskUAAAAABJRU5ErkJggg==",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"weighted_results = weighted_model.evaluate(test_features, test_labels,\n",
" batch_size=BATCH_SIZE, verbose=0)\n",
"for name, value in zip(weighted_model.metrics_names, weighted_results):\n",
" print(name, ': ', value)\n",
"print()\n",
"\n",
"plot_cm(test_labels, test_predictions_weighted)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PTh1rtDn8r4-"
},
"source": [
"Here you can see that with class weights the accuracy and precision are lower because there are more false positives, but conversely the recall and AUC are higher because the model also found more true positives. Despite having lower accuracy, this model has higher recall (and identifies more fraudulent transactions than the baseline model at threshold 50%). Of course, there is a cost to both types of error (you wouldn't want to bug users by flagging too many legitimate transactions as fraudulent, either). Carefully consider the trade-offs between these different types of errors for your application.\n",
"\n",
"Compared to the baseline model with changed threshold, the class weighted model is clearly inferior. The superiority of the baseline model is further confirmed by the lower test loss value (cross entropy and mean squared error) and additionally can be seen by plotting the ROC curves of both models together."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hXDAwyr0HYdX"
},
"source": [
"### Plot the ROC"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.075664Z",
"iopub.status.busy": "2024-08-20T01:25:27.075411Z",
"iopub.status.idle": "2024-08-20T01:25:27.366658Z",
"shell.execute_reply": "2024-08-20T01:25:27.366004Z"
},
"id": "3hzScIVZS1Xm"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_roc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
"plot_roc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
"\n",
"plot_roc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
"plot_roc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
"\n",
"\n",
"plt.legend(loc='lower right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_0krS8g1OTbD"
},
"source": [
"### Plot the PRC"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.370552Z",
"iopub.status.busy": "2024-08-20T01:25:27.370294Z",
"iopub.status.idle": "2024-08-20T01:25:27.686226Z",
"shell.execute_reply": "2024-08-20T01:25:27.685277Z"
},
"id": "7jHnmVebOWOC"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_prc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
"plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
"\n",
"plot_prc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
"plot_prc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
"\n",
"\n",
"plt.legend(loc='lower right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "5ysRtr6xHnXP"
},
"source": [
"## Oversampling"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "18VUHNc-UF5w"
},
"source": [
"### Oversample the minority class\n",
"\n",
"A related approach would be to resample the dataset by oversampling the minority class."
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.690561Z",
"iopub.status.busy": "2024-08-20T01:25:27.690309Z",
"iopub.status.idle": "2024-08-20T01:25:27.718468Z",
"shell.execute_reply": "2024-08-20T01:25:27.717633Z"
},
"id": "sHirNp6u7OWp"
},
"outputs": [],
"source": [
"pos_features = train_features[bool_train_labels]\n",
"neg_features = train_features[~bool_train_labels]\n",
"\n",
"pos_labels = train_labels[bool_train_labels]\n",
"neg_labels = train_labels[~bool_train_labels]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "WgBVbX7P7QrL"
},
"source": [
"#### Using NumPy\n",
"\n",
"You can balance the dataset manually by choosing the right number of random\n",
"indices from the positive examples:"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.722795Z",
"iopub.status.busy": "2024-08-20T01:25:27.722238Z",
"iopub.status.idle": "2024-08-20T01:25:27.748126Z",
"shell.execute_reply": "2024-08-20T01:25:27.747381Z"
},
"id": "BUzGjSkwqT88"
},
"outputs": [
{
"data": {
"text/plain": [
"(181968, 29)"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ids = np.arange(len(pos_features))\n",
"choices = np.random.choice(ids, len(neg_features))\n",
"\n",
"res_pos_features = pos_features[choices]\n",
"res_pos_labels = pos_labels[choices]\n",
"\n",
"res_pos_features.shape"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.751772Z",
"iopub.status.busy": "2024-08-20T01:25:27.751147Z",
"iopub.status.idle": "2024-08-20T01:25:27.862130Z",
"shell.execute_reply": "2024-08-20T01:25:27.861347Z"
},
"id": "7ie_FFet6cep"
},
"outputs": [
{
"data": {
"text/plain": [
"(363936, 29)"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"resampled_features = np.concatenate([res_pos_features, neg_features], axis=0)\n",
"resampled_labels = np.concatenate([res_pos_labels, neg_labels], axis=0)\n",
"\n",
"order = np.arange(len(resampled_labels))\n",
"np.random.shuffle(order)\n",
"resampled_features = resampled_features[order]\n",
"resampled_labels = resampled_labels[order]\n",
"\n",
"resampled_features.shape"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "IYfJe2Kc-FAz"
},
"source": [
"#### Using `tf.data`"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "usyixaST8v5P"
},
"source": [
"If you're using `tf.data` the easiest way to produce balanced examples is to start with a `positive` and a `negative` dataset, and merge them. See [the tf.data guide](../../guide/data.ipynb) for more examples."
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.866195Z",
"iopub.status.busy": "2024-08-20T01:25:27.865410Z",
"iopub.status.idle": "2024-08-20T01:25:27.985982Z",
"shell.execute_reply": "2024-08-20T01:25:27.985299Z"
},
"id": "yF4OZ-rI6xb6"
},
"outputs": [],
"source": [
"BUFFER_SIZE = 100000\n",
"\n",
"def make_ds(features, labels):\n",
" ds = tf.data.Dataset.from_tensor_slices((features, labels))#.cache()\n",
" ds = ds.shuffle(BUFFER_SIZE).repeat()\n",
" return ds\n",
"\n",
"pos_ds = make_ds(pos_features, pos_labels)\n",
"neg_ds = make_ds(neg_features, neg_labels)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "RNQUx-OA-oJc"
},
"source": [
"Each dataset provides `(feature, label)` pairs:"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:27.989797Z",
"iopub.status.busy": "2024-08-20T01:25:27.989510Z",
"iopub.status.idle": "2024-08-20T01:25:28.006413Z",
"shell.execute_reply": "2024-08-20T01:25:28.005816Z"
},
"id": "llXc9rNH7Fbz"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Features:\n",
" [-5. 5. -5. 5. -5. -1.79067376\n",
" -5. 0.8091474 -5. -5. 5. -5.\n",
" 0.77844233 -5. -0.38533935 -5. -5. -5.\n",
" 0.8008565 1.2865953 -3.24913168 1.43279414 1.794716 -1.72782919\n",
" -0.20834708 1.3608197 5. -4.32439607 -1.45407944]\n",
"\n",
"Label: [1]\n"
]
}
],
"source": [
"for features, label in pos_ds.take(1):\n",
" print(\"Features:\\n\", features.numpy())\n",
" print()\n",
" print(\"Label: \", label.numpy())"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sLEfjZO0-vbN"
},
"source": [
"Merge the two together using `tf.data.Dataset.sample_from_datasets`:"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:28.009437Z",
"iopub.status.busy": "2024-08-20T01:25:28.009201Z",
"iopub.status.idle": "2024-08-20T01:25:28.030522Z",
"shell.execute_reply": "2024-08-20T01:25:28.029899Z"
},
"id": "e7w9UQPT9wzE"
},
"outputs": [],
"source": [
"resampled_ds = tf.data.Dataset.sample_from_datasets([pos_ds, neg_ds], weights=[0.5, 0.5])\n",
"resampled_ds = resampled_ds.batch(BATCH_SIZE).prefetch(2)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:28.033541Z",
"iopub.status.busy": "2024-08-20T01:25:28.033310Z",
"iopub.status.idle": "2024-08-20T01:25:28.316272Z",
"shell.execute_reply": "2024-08-20T01:25:28.315533Z"
},
"id": "EWXARdTdAuQK"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.509765625\n"
]
}
],
"source": [
"for features, label in resampled_ds.take(1):\n",
" print(label.numpy().mean())"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "irgqf3YxAyN0"
},
"source": [
"To use this dataset, you'll need the number of steps per epoch.\n",
"\n",
"The definition of \"epoch\" in this case is less clear. Say it's the number of batches required to see each negative example once:"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:28.319689Z",
"iopub.status.busy": "2024-08-20T01:25:28.319388Z",
"iopub.status.idle": "2024-08-20T01:25:28.324246Z",
"shell.execute_reply": "2024-08-20T01:25:28.323669Z"
},
"id": "xH-7K46AAxpq"
},
"outputs": [
{
"data": {
"text/plain": [
"278"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"resampled_steps_per_epoch = int(np.ceil(2.0*neg/BATCH_SIZE))\n",
"resampled_steps_per_epoch"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "XZ1BvEpcBVHP"
},
"source": [
"### Train on the oversampled data\n",
"\n",
"Now try training the model with the resampled data set instead of using class weights to see how these methods compare.\n",
"\n",
"Note: Because the data was balanced by replicating the positive examples, the total dataset size is larger, and each epoch runs for more training steps."
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:25:28.327320Z",
"iopub.status.busy": "2024-08-20T01:25:28.327074Z",
"iopub.status.idle": "2024-08-20T01:26:36.564548Z",
"shell.execute_reply": "2024-08-20T01:26:36.563745Z"
},
"id": "soRQ89JYqd6b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/100\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
" super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m18:23\u001b[0m 4s/step - Brier score: 0.0114 - accuracy: 0.9830 - auc: 0.9832 - cross entropy: 0.0438 - fn: 387.0000 - fp: 619.0000 - loss: 0.8446 - prc: 0.6497 - precision: 0.5465 - recall: 0.6584 - tn: 57258.0000 - tp: 746.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 6/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 13ms/step - Brier score: 0.0314 - accuracy: 0.9510 - auc: 0.9708 - cross entropy: 0.1010 - fn: 1238.1666 - fp: 1974.6666 - loss: 0.8129 - prc: 0.6686 - precision: 0.5477 - recall: 0.6595 - tn: 58505.1680 - tp: 2412.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 9/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 15ms/step - Brier score: 0.0410 - accuracy: 0.9357 - auc: 0.9641 - cross entropy: 0.1282 - fn: 1694.3334 - fp: 2773.6667 - loss: 0.7977 - prc: 0.6802 - precision: 0.5521 - recall: 0.6668 - tn: 59262.7773 - tp: 3471.2222"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 12/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 16ms/step - Brier score: 0.0494 - accuracy: 0.9223 - auc: 0.9580 - cross entropy: 0.1517 - fn: 2124.3333 - fp: 3569.1667 - loss: 0.7851 - prc: 0.6898 - precision: 0.5558 - recall: 0.6739 - tn: 60027.0820 - tp: 4553.4165"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 15/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0566 - accuracy: 0.9106 - auc: 0.9525 - cross entropy: 0.1723 - fn: 2535.9333 - fp: 4354.3335 - loss: 0.7743 - prc: 0.6981 - precision: 0.5595 - recall: 0.6806 - tn: 60790.3320 - tp: 5665.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 18/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0630 - accuracy: 0.9003 - auc: 0.9477 - cross entropy: 0.1903 - fn: 2921.9443 - fp: 5134.0557 - loss: 0.7645 - prc: 0.7057 - precision: 0.5630 - recall: 0.6872 - tn: 61556.7773 - tp: 6805.2222"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 21/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0687 - accuracy: 0.8912 - auc: 0.9433 - cross entropy: 0.2063 - fn: 3287.7620 - fp: 5908.2856 - loss: 0.7555 - prc: 0.7127 - precision: 0.5662 - recall: 0.6935 - tn: 62331.8086 - tp: 7962.1431"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 24/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0737 - accuracy: 0.8830 - auc: 0.9395 - cross entropy: 0.2204 - fn: 3636.7917 - fp: 6672.7085 - loss: 0.7470 - prc: 0.7195 - precision: 0.5694 - recall: 0.6994 - tn: 63108.8320 - tp: 9143.6670"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 27/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0781 - accuracy: 0.8757 - auc: 0.9362 - cross entropy: 0.2330 - fn: 3970.1853 - fp: 7428.5928 - loss: 0.7389 - prc: 0.7258 - precision: 0.5725 - recall: 0.7051 - tn: 63887.8906 - tp: 10347.3330"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 30/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0821 - accuracy: 0.8692 - auc: 0.9331 - cross entropy: 0.2442 - fn: 4290.2998 - fp: 8171.1333 - loss: 0.7314 - prc: 0.7317 - precision: 0.5755 - recall: 0.7104 - tn: 64679.8008 - tp: 11564.7666"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 33/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0857 - accuracy: 0.8634 - auc: 0.9304 - cross entropy: 0.2544 - fn: 4597.8486 - fp: 8905.6973 - loss: 0.7242 - prc: 0.7373 - precision: 0.5783 - recall: 0.7155 - tn: 65480.7266 - tp: 12793.7275"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 36/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0890 - accuracy: 0.8581 - auc: 0.9279 - cross entropy: 0.2637 - fn: 4891.3335 - fp: 9632.4443 - loss: 0.7175 - prc: 0.7425 - precision: 0.5810 - recall: 0.7203 - tn: 66290.0859 - tp: 14036.1387"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 39/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0920 - accuracy: 0.8533 - auc: 0.9257 - cross entropy: 0.2721 - fn: 5173.6411 - fp: 10350.4619 - loss: 0.7111 - prc: 0.7474 - precision: 0.5836 - recall: 0.7248 - tn: 67111.7188 - tp: 15286.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 42/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0947 - accuracy: 0.8489 - auc: 0.9237 - cross entropy: 0.2797 - fn: 5449.9521 - fp: 11057.8096 - loss: 0.7051 - prc: 0.7521 - precision: 0.5862 - recall: 0.7291 - tn: 67942.8594 - tp: 16543.3809"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 45/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0972 - accuracy: 0.8450 - auc: 0.9219 - cross entropy: 0.2867 - fn: 5717.6445 - fp: 11753.1777 - loss: 0.6993 - prc: 0.7565 - precision: 0.5886 - recall: 0.7331 - tn: 68787.0703 - tp: 17808.1113"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 48/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0994 - accuracy: 0.8414 - auc: 0.9203 - cross entropy: 0.2931 - fn: 5976.9375 - fp: 12437.7705 - loss: 0.6938 - prc: 0.7607 - precision: 0.5910 - recall: 0.7370 - tn: 69643.0234 - tp: 19080.2715"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 51/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.1015 - accuracy: 0.8381 - auc: 0.9188 - cross entropy: 0.2990 - fn: 6229.6860 - fp: 13112.8828 - loss: 0.6885 - prc: 0.7646 - precision: 0.5933 - recall: 0.7406 - tn: 70509.7656 - tp: 20357.6660"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 54/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.1034 - accuracy: 0.8351 - auc: 0.9175 - cross entropy: 0.3045 - fn: 6477.6479 - fp: 13778.5186 - loss: 0.6835 - prc: 0.7684 - precision: 0.5956 - recall: 0.7440 - tn: 71385.4297 - tp: 21640.4082"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 57/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.1052 - accuracy: 0.8323 - auc: 0.9163 - cross entropy: 0.3095 - fn: 6720.0703 - fp: 14432.9473 - loss: 0.6787 - prc: 0.7720 - precision: 0.5978 - recall: 0.7473 - tn: 72271.8594 - tp: 22929.1230"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 60/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 18ms/step - Brier score: 0.1068 - accuracy: 0.8298 - auc: 0.9152 - cross entropy: 0.3142 - fn: 6960.0332 - fp: 15076.7002 - loss: 0.6740 - prc: 0.7754 - precision: 0.6000 - recall: 0.7504 - tn: 73166.9688 - tp: 24222.3008"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 63/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 18ms/step - Brier score: 0.1083 - accuracy: 0.8274 - auc: 0.9142 - cross entropy: 0.3185 - fn: 7197.8413 - fp: 15711.3652 - loss: 0.6695 - prc: 0.7787 - precision: 0.6021 - recall: 0.7533 - tn: 74070.9844 - tp: 25517.8086"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 66/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 18ms/step - Brier score: 0.1097 - accuracy: 0.8253 - auc: 0.9133 - cross entropy: 0.3225 - fn: 7433.5605 - fp: 16335.0459 - loss: 0.6652 - prc: 0.7818 - precision: 0.6041 - recall: 0.7560 - tn: 74984.3750 - tp: 26817.0156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 69/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 18ms/step - Brier score: 0.1110 - accuracy: 0.8233 - auc: 0.9124 - cross entropy: 0.3262 - fn: 7667.2173 - fp: 16948.1016 - loss: 0.6610 - prc: 0.7848 - precision: 0.6062 - recall: 0.7586 - tn: 75908.5234 - tp: 28118.1602"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 72/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 18ms/step - Brier score: 0.1122 - accuracy: 0.8215 - auc: 0.9117 - cross entropy: 0.3297 - fn: 7898.5693 - fp: 17552.4590 - loss: 0.6570 - prc: 0.7876 - precision: 0.6082 - recall: 0.7611 - tn: 76841.5938 - tp: 29421.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 75/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1133 - accuracy: 0.8198 - auc: 0.9110 - cross entropy: 0.3329 - fn: 8128.2002 - fp: 18145.9863 - loss: 0.6530 - prc: 0.7904 - precision: 0.6101 - recall: 0.7635 - tn: 77785.1875 - tp: 30726.6270"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 78/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1143 - accuracy: 0.8182 - auc: 0.9103 - cross entropy: 0.3359 - fn: 8355.2949 - fp: 18729.6289 - loss: 0.6492 - prc: 0.7930 - precision: 0.6120 - recall: 0.7657 - tn: 78738.2422 - tp: 32034.8340"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 81/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1153 - accuracy: 0.8168 - auc: 0.9097 - cross entropy: 0.3387 - fn: 8580.0244 - fp: 19305.8398 - loss: 0.6455 - prc: 0.7956 - precision: 0.6139 - recall: 0.7679 - tn: 79700.7656 - tp: 33343.3711"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 84/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1162 - accuracy: 0.8154 - auc: 0.9092 - cross entropy: 0.3413 - fn: 8803.5000 - fp: 19873.5957 - loss: 0.6419 - prc: 0.7980 - precision: 0.6158 - recall: 0.7699 - tn: 80669.8125 - tp: 34655.0938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 87/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1170 - accuracy: 0.8142 - auc: 0.9087 - cross entropy: 0.3438 - fn: 9026.4365 - fp: 20432.3906 - loss: 0.6384 - prc: 0.8004 - precision: 0.6176 - recall: 0.7719 - tn: 81644.9531 - tp: 35970.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 90/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1178 - accuracy: 0.8131 - auc: 0.9083 - cross entropy: 0.3460 - fn: 9248.1113 - fp: 20982.3008 - loss: 0.6350 - prc: 0.8027 - precision: 0.6194 - recall: 0.7737 - tn: 82629.1016 - tp: 37286.4883"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 93/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1185 - accuracy: 0.8120 - auc: 0.9079 - cross entropy: 0.3482 - fn: 9468.8281 - fp: 21523.0000 - loss: 0.6317 - prc: 0.8049 - precision: 0.6211 - recall: 0.7755 - tn: 83623.7969 - tp: 38602.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 96/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1192 - accuracy: 0.8111 - auc: 0.9075 - cross entropy: 0.3502 - fn: 9687.8643 - fp: 22055.5215 - loss: 0.6285 - prc: 0.8070 - precision: 0.6229 - recall: 0.7772 - tn: 84627.4766 - tp: 39919.1367"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 99/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1198 - accuracy: 0.8102 - auc: 0.9072 - cross entropy: 0.3520 - fn: 9905.2227 - fp: 22579.7676 - loss: 0.6253 - prc: 0.8091 - precision: 0.6246 - recall: 0.7789 - tn: 85639.8906 - tp: 41237.1211"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m102/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1204 - accuracy: 0.8094 - auc: 0.9069 - cross entropy: 0.3538 - fn: 10121.7549 - fp: 23096.2344 - loss: 0.6222 - prc: 0.8111 - precision: 0.6263 - recall: 0.7805 - tn: 86657.8047 - tp: 42558.2070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m105/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1209 - accuracy: 0.8086 - auc: 0.9067 - cross entropy: 0.3554 - fn: 10337.2949 - fp: 23604.3145 - loss: 0.6192 - prc: 0.8131 - precision: 0.6280 - recall: 0.7820 - tn: 87681.9609 - tp: 43882.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m108/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1214 - accuracy: 0.8079 - auc: 0.9064 - cross entropy: 0.3569 - fn: 10551.8057 - fp: 24104.7324 - loss: 0.6162 - prc: 0.8150 - precision: 0.6296 - recall: 0.7835 - tn: 88711.4141 - tp: 45210.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m111/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1219 - accuracy: 0.8073 - auc: 0.9063 - cross entropy: 0.3583 - fn: 10765.0088 - fp: 24597.9277 - loss: 0.6133 - prc: 0.8168 - precision: 0.6313 - recall: 0.7849 - tn: 89747.1406 - tp: 46539.9180"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m114/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1223 - accuracy: 0.8067 - auc: 0.9061 - cross entropy: 0.3596 - fn: 10976.6406 - fp: 25084.7988 - loss: 0.6105 - prc: 0.8186 - precision: 0.6329 - recall: 0.7863 - tn: 90789.4922 - tp: 47871.0703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m117/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.1227 - accuracy: 0.8062 - auc: 0.9059 - cross entropy: 0.3609 - fn: 11187.4102 - fp: 25563.9746 - loss: 0.6077 - prc: 0.8204 - precision: 0.6345 - recall: 0.7877 - tn: 91840.2969 - tp: 49202.3164"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m120/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1231 - accuracy: 0.8057 - auc: 0.9058 - cross entropy: 0.3620 - fn: 11397.1914 - fp: 26036.4492 - loss: 0.6050 - prc: 0.8221 - precision: 0.6360 - recall: 0.7890 - tn: 92898.7891 - tp: 50533.5664"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m123/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1235 - accuracy: 0.8053 - auc: 0.9057 - cross entropy: 0.3631 - fn: 11605.6338 - fp: 26503.6270 - loss: 0.6023 - prc: 0.8237 - precision: 0.6376 - recall: 0.7902 - tn: 93963.3203 - tp: 51865.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m126/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1238 - accuracy: 0.8049 - auc: 0.9056 - cross entropy: 0.3641 - fn: 11813.4287 - fp: 26963.2930 - loss: 0.5997 - prc: 0.8253 - precision: 0.6391 - recall: 0.7914 - tn: 95036.1328 - tp: 53197.1445"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m129/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1241 - accuracy: 0.8045 - auc: 0.9056 - cross entropy: 0.3650 - fn: 12020.2480 - fp: 27415.5430 - loss: 0.5971 - prc: 0.8269 - precision: 0.6406 - recall: 0.7926 - tn: 96115.8594 - tp: 54530.3477"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m132/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1244 - accuracy: 0.8042 - auc: 0.9055 - cross entropy: 0.3659 - fn: 12226.4014 - fp: 27861.4922 - loss: 0.5946 - prc: 0.8284 - precision: 0.6421 - recall: 0.7938 - tn: 97201.6172 - tp: 55864.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m135/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1246 - accuracy: 0.8039 - auc: 0.9055 - cross entropy: 0.3667 - fn: 12432.1260 - fp: 28301.2148 - loss: 0.5921 - prc: 0.8299 - precision: 0.6436 - recall: 0.7949 - tn: 98292.8203 - tp: 57199.8359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m138/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1248 - accuracy: 0.8037 - auc: 0.9055 - cross entropy: 0.3675 - fn: 12637.6670 - fp: 28734.2754 - loss: 0.5896 - prc: 0.8314 - precision: 0.6451 - recall: 0.7959 - tn: 99389.4531 - tp: 58536.6094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m141/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1251 - accuracy: 0.8034 - auc: 0.9054 - cross entropy: 0.3682 - fn: 12842.8799 - fp: 29161.4395 - loss: 0.5872 - prc: 0.8328 - precision: 0.6465 - recall: 0.7970 - tn: 100492.8828 - tp: 59872.8008"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m144/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1252 - accuracy: 0.8032 - auc: 0.9054 - cross entropy: 0.3688 - fn: 13047.3193 - fp: 29582.9160 - loss: 0.5849 - prc: 0.8342 - precision: 0.6480 - recall: 0.7980 - tn: 101602.5312 - tp: 61209.2305"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m147/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1254 - accuracy: 0.8031 - auc: 0.9055 - cross entropy: 0.3694 - fn: 13251.1768 - fp: 29998.1367 - loss: 0.5826 - prc: 0.8356 - precision: 0.6494 - recall: 0.7990 - tn: 102719.1875 - tp: 62545.5039"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m150/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1256 - accuracy: 0.8029 - auc: 0.9055 - cross entropy: 0.3700 - fn: 13454.3936 - fp: 30407.8672 - loss: 0.5803 - prc: 0.8369 - precision: 0.6508 - recall: 0.7999 - tn: 103841.8438 - tp: 63881.8945"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m153/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1257 - accuracy: 0.8028 - auc: 0.9055 - cross entropy: 0.3705 - fn: 13657.1895 - fp: 30811.3652 - loss: 0.5780 - prc: 0.8382 - precision: 0.6522 - recall: 0.8009 - tn: 104969.6875 - tp: 65219.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m156/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1259 - accuracy: 0.8027 - auc: 0.9056 - cross entropy: 0.3709 - fn: 13859.4932 - fp: 31208.9043 - loss: 0.5758 - prc: 0.8395 - precision: 0.6535 - recall: 0.8018 - tn: 106103.3594 - tp: 66558.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m159/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1260 - accuracy: 0.8027 - auc: 0.9056 - cross entropy: 0.3714 - fn: 14061.4531 - fp: 31600.8672 - loss: 0.5736 - prc: 0.8407 - precision: 0.6549 - recall: 0.8027 - tn: 107242.5938 - tp: 67897.0859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m162/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1261 - accuracy: 0.8026 - auc: 0.9057 - cross entropy: 0.3718 - fn: 14262.8887 - fp: 31987.6855 - loss: 0.5715 - prc: 0.8419 - precision: 0.6562 - recall: 0.8035 - tn: 108387.2500 - tp: 69236.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m165/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1262 - accuracy: 0.8026 - auc: 0.9058 - cross entropy: 0.3721 - fn: 14464.0420 - fp: 32369.4844 - loss: 0.5694 - prc: 0.8431 - precision: 0.6576 - recall: 0.8043 - tn: 109536.6094 - tp: 70575.8594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m168/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1263 - accuracy: 0.8025 - auc: 0.9059 - cross entropy: 0.3724 - fn: 14664.5830 - fp: 32746.1484 - loss: 0.5673 - prc: 0.8443 - precision: 0.6589 - recall: 0.8052 - tn: 110691.1250 - tp: 71916.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m171/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.1263 - accuracy: 0.8025 - auc: 0.9060 - cross entropy: 0.3727 - fn: 14865.1465 - fp: 33117.3750 - loss: 0.5652 - prc: 0.8454 - precision: 0.6602 - recall: 0.8060 - tn: 111850.9219 - tp: 73256.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m174/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1264 - accuracy: 0.8026 - auc: 0.9060 - cross entropy: 0.3730 - fn: 15065.4365 - fp: 33483.3320 - loss: 0.5632 - prc: 0.8466 - precision: 0.6615 - recall: 0.8067 - tn: 113015.7266 - tp: 74597.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m177/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1264 - accuracy: 0.8026 - auc: 0.9061 - cross entropy: 0.3732 - fn: 15265.6211 - fp: 33844.2266 - loss: 0.5612 - prc: 0.8477 - precision: 0.6628 - recall: 0.8075 - tn: 114185.3984 - tp: 75938.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m180/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8026 - auc: 0.9063 - cross entropy: 0.3734 - fn: 15465.4277 - fp: 34200.0938 - loss: 0.5592 - prc: 0.8487 - precision: 0.6641 - recall: 0.8082 - tn: 115360.2266 - tp: 77280.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m183/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8027 - auc: 0.9064 - cross entropy: 0.3736 - fn: 15664.8418 - fp: 34551.1328 - loss: 0.5573 - prc: 0.8498 - precision: 0.6653 - recall: 0.8089 - tn: 116539.9531 - tp: 78622.0781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m186/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8028 - auc: 0.9065 - cross entropy: 0.3737 - fn: 15863.8711 - fp: 34897.5391 - loss: 0.5554 - prc: 0.8508 - precision: 0.6666 - recall: 0.8096 - tn: 117723.1094 - tp: 79965.4844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m189/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8029 - auc: 0.9066 - cross entropy: 0.3739 - fn: 16062.3389 - fp: 35239.4180 - loss: 0.5535 - prc: 0.8519 - precision: 0.6678 - recall: 0.8103 - tn: 118910.8672 - tp: 81309.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m192/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8030 - auc: 0.9067 - cross entropy: 0.3740 - fn: 16260.4482 - fp: 35576.6992 - loss: 0.5516 - prc: 0.8529 - precision: 0.6690 - recall: 0.8110 - tn: 120103.6797 - tp: 82653.1719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m195/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8031 - auc: 0.9069 - cross entropy: 0.3741 - fn: 16458.1992 - fp: 35909.7188 - loss: 0.5498 - prc: 0.8539 - precision: 0.6703 - recall: 0.8117 - tn: 121301.1172 - tp: 83996.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m198/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8032 - auc: 0.9070 - cross entropy: 0.3741 - fn: 16655.6719 - fp: 36238.4766 - loss: 0.5479 - prc: 0.8548 - precision: 0.6715 - recall: 0.8123 - tn: 122502.1953 - tp: 85341.6562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m201/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8033 - auc: 0.9072 - cross entropy: 0.3742 - fn: 16852.8555 - fp: 36562.9609 - loss: 0.5461 - prc: 0.8558 - precision: 0.6727 - recall: 0.8129 - tn: 123707.5781 - tp: 86686.6094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m204/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1265 - accuracy: 0.8034 - auc: 0.9073 - cross entropy: 0.3742 - fn: 17049.6465 - fp: 36883.3047 - loss: 0.5443 - prc: 0.8567 - precision: 0.6738 - recall: 0.8136 - tn: 124916.8516 - tp: 88032.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m207/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1264 - accuracy: 0.8036 - auc: 0.9074 - cross entropy: 0.3742 - fn: 17245.8848 - fp: 37199.3477 - loss: 0.5426 - prc: 0.8576 - precision: 0.6750 - recall: 0.8142 - tn: 126129.9922 - tp: 89378.7812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m210/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1264 - accuracy: 0.8037 - auc: 0.9076 - cross entropy: 0.3742 - fn: 17441.7051 - fp: 37511.3398 - loss: 0.5408 - prc: 0.8585 - precision: 0.6762 - recall: 0.8148 - tn: 127347.0469 - tp: 90725.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m213/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1264 - accuracy: 0.8039 - auc: 0.9078 - cross entropy: 0.3741 - fn: 17637.1777 - fp: 37819.0742 - loss: 0.5391 - prc: 0.8594 - precision: 0.6773 - recall: 0.8153 - tn: 128568.9297 - tp: 92072.8203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m216/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1263 - accuracy: 0.8041 - auc: 0.9079 - cross entropy: 0.3741 - fn: 17832.2031 - fp: 38122.4805 - loss: 0.5374 - prc: 0.8603 - precision: 0.6785 - recall: 0.8159 - tn: 129795.3047 - tp: 93420.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m219/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1263 - accuracy: 0.8043 - auc: 0.9081 - cross entropy: 0.3740 - fn: 18027.2246 - fp: 38421.8594 - loss: 0.5357 - prc: 0.8611 - precision: 0.6796 - recall: 0.8165 - tn: 131025.2344 - tp: 94767.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m222/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1262 - accuracy: 0.8044 - auc: 0.9082 - cross entropy: 0.3739 - fn: 18221.8477 - fp: 38717.4922 - loss: 0.5341 - prc: 0.8620 - precision: 0.6808 - recall: 0.8170 - tn: 132258.5469 - tp: 96116.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m225/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.1261 - accuracy: 0.8046 - auc: 0.9084 - cross entropy: 0.3738 - fn: 18416.0273 - fp: 39009.4961 - loss: 0.5324 - prc: 0.8628 - precision: 0.6819 - recall: 0.8176 - tn: 133495.8750 - tp: 97464.6016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m228/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1261 - accuracy: 0.8048 - auc: 0.9086 - cross entropy: 0.3737 - fn: 18609.8418 - fp: 39297.8164 - loss: 0.5308 - prc: 0.8636 - precision: 0.6830 - recall: 0.8181 - tn: 134736.6875 - tp: 98813.6641"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m231/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1260 - accuracy: 0.8050 - auc: 0.9087 - cross entropy: 0.3736 - fn: 18803.2344 - fp: 39582.7148 - loss: 0.5292 - prc: 0.8644 - precision: 0.6841 - recall: 0.8186 - tn: 135981.2188 - tp: 100162.8281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m233/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1260 - accuracy: 0.8052 - auc: 0.9089 - cross entropy: 0.3735 - fn: 18931.9355 - fp: 39770.7305 - loss: 0.5281 - prc: 0.8650 - precision: 0.6848 - recall: 0.8189 - tn: 136812.3438 - tp: 101062.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m236/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1259 - accuracy: 0.8054 - auc: 0.9090 - cross entropy: 0.3734 - fn: 19124.7637 - fp: 40050.3516 - loss: 0.5265 - prc: 0.8658 - precision: 0.6859 - recall: 0.8195 - tn: 138062.3281 - tp: 102412.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m239/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1258 - accuracy: 0.8056 - auc: 0.9092 - cross entropy: 0.3732 - fn: 19317.1094 - fp: 40327.1094 - loss: 0.5250 - prc: 0.8665 - precision: 0.6870 - recall: 0.8200 - tn: 139316.3281 - tp: 103761.4453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m242/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1257 - accuracy: 0.8058 - auc: 0.9094 - cross entropy: 0.3731 - fn: 19509.1523 - fp: 40600.4062 - loss: 0.5234 - prc: 0.8673 - precision: 0.6881 - recall: 0.8204 - tn: 140573.7812 - tp: 105110.6641"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m245/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1256 - accuracy: 0.8061 - auc: 0.9096 - cross entropy: 0.3729 - fn: 19700.7559 - fp: 40870.5039 - loss: 0.5219 - prc: 0.8680 - precision: 0.6891 - recall: 0.8209 - tn: 141834.5938 - tp: 106460.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m248/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1255 - accuracy: 0.8063 - auc: 0.9097 - cross entropy: 0.3727 - fn: 19892.1094 - fp: 41137.6992 - loss: 0.5204 - prc: 0.8688 - precision: 0.6902 - recall: 0.8214 - tn: 143098.8281 - tp: 107809.3672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m251/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1254 - accuracy: 0.8065 - auc: 0.9099 - cross entropy: 0.3726 - fn: 20083.0527 - fp: 41401.7773 - loss: 0.5189 - prc: 0.8695 - precision: 0.6912 - recall: 0.8219 - tn: 144366.6094 - tp: 109158.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m254/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1254 - accuracy: 0.8068 - auc: 0.9101 - cross entropy: 0.3724 - fn: 20273.5859 - fp: 41662.7031 - loss: 0.5174 - prc: 0.8702 - precision: 0.6923 - recall: 0.8223 - tn: 145637.7656 - tp: 110507.9375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m257/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1253 - accuracy: 0.8070 - auc: 0.9103 - cross entropy: 0.3722 - fn: 20463.8281 - fp: 41920.4844 - loss: 0.5159 - prc: 0.8709 - precision: 0.6933 - recall: 0.8228 - tn: 146912.5781 - tp: 111857.1172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m260/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1251 - accuracy: 0.8072 - auc: 0.9104 - cross entropy: 0.3719 - fn: 20653.6309 - fp: 42175.3984 - loss: 0.5145 - prc: 0.8716 - precision: 0.6943 - recall: 0.8232 - tn: 148190.5469 - tp: 113206.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m263/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1250 - accuracy: 0.8075 - auc: 0.9106 - cross entropy: 0.3717 - fn: 20843.1484 - fp: 42427.5391 - loss: 0.5131 - prc: 0.8723 - precision: 0.6953 - recall: 0.8236 - tn: 149471.7812 - tp: 114555.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m266/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1249 - accuracy: 0.8077 - auc: 0.9108 - cross entropy: 0.3715 - fn: 21032.3457 - fp: 42676.5586 - loss: 0.5116 - prc: 0.8730 - precision: 0.6963 - recall: 0.8241 - tn: 150755.9062 - tp: 115905.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m269/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1248 - accuracy: 0.8080 - auc: 0.9110 - cross entropy: 0.3713 - fn: 21221.2148 - fp: 42922.7969 - loss: 0.5102 - prc: 0.8736 - precision: 0.6973 - recall: 0.8245 - tn: 152042.8125 - tp: 117255.1719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m272/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1247 - accuracy: 0.8082 - auc: 0.9112 - cross entropy: 0.3710 - fn: 21409.9258 - fp: 43166.6055 - loss: 0.5088 - prc: 0.8743 - precision: 0.6983 - recall: 0.8249 - tn: 153332.0000 - tp: 118605.4688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m275/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1246 - accuracy: 0.8085 - auc: 0.9114 - cross entropy: 0.3708 - fn: 21598.2949 - fp: 43407.5430 - loss: 0.5075 - prc: 0.8749 - precision: 0.6993 - recall: 0.8253 - tn: 154624.7344 - tp: 119955.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1245 - accuracy: 0.8088 - auc: 0.9115 - cross entropy: 0.3705 - fn: 21786.6875 - fp: 43645.6328 - loss: 0.5061 - prc: 0.8756 - precision: 0.7002 - recall: 0.8257 - tn: 155919.5312 - tp: 121306.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 31ms/step - Brier score: 0.1245 - accuracy: 0.8089 - auc: 0.9116 - cross entropy: 0.3704 - fn: 21849.0215 - fp: 43724.1445 - loss: 0.5056 - prc: 0.8758 - precision: 0.7006 - recall: 0.8258 - tn: 156348.1719 - tp: 121753.3125 - val_Brier score: 0.0452 - val_accuracy: 0.9760 - val_auc: 0.9818 - val_cross entropy: 0.2065 - val_fn: 5.0000 - val_fp: 1090.0000 - val_loss: 0.2065 - val_prc: 0.7920 - val_precision: 0.0660 - val_recall: 0.9390 - val_tn: 44397.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - Brier score: 0.0763 - accuracy: 0.8984 - auc: 0.9599 - cross entropy: 0.2509 - fn: 111.0000 - fp: 97.0000 - loss: 0.2509 - prc: 0.9688 - precision: 0.9020 - recall: 0.8894 - tn: 947.0000 - tp: 893.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 14ms/step - Brier score: 0.0741 - accuracy: 0.9022 - auc: 0.9626 - cross entropy: 0.2428 - fn: 333.4000 - fp: 261.2000 - loss: 0.2428 - prc: 0.9703 - precision: 0.9094 - recall: 0.8891 - tn: 2868.0000 - tp: 2681.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 16ms/step - Brier score: 0.0732 - accuracy: 0.9040 - auc: 0.9635 - cross entropy: 0.2400 - fn: 500.1250 - fp: 371.6250 - loss: 0.2400 - prc: 0.9712 - precision: 0.9131 - recall: 0.8897 - tn: 4294.0000 - tp: 4050.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0729 - accuracy: 0.9045 - auc: 0.9638 - cross entropy: 0.2389 - fn: 669.1818 - fp: 489.6364 - loss: 0.2389 - prc: 0.9715 - precision: 0.9145 - recall: 0.8896 - tn: 5721.8184 - tp: 5407.3638"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0726 - accuracy: 0.9050 - auc: 0.9640 - cross entropy: 0.2381 - fn: 838.2857 - fp: 604.7857 - loss: 0.2381 - prc: 0.9717 - precision: 0.9156 - recall: 0.8896 - tn: 7149.8569 - tp: 6767.0713"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0724 - accuracy: 0.9054 - auc: 0.9642 - cross entropy: 0.2374 - fn: 1008.1177 - fp: 717.5294 - loss: 0.2374 - prc: 0.9719 - precision: 0.9166 - recall: 0.8896 - tn: 8571.8232 - tp: 8134.5293"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0722 - accuracy: 0.9056 - auc: 0.9644 - cross entropy: 0.2369 - fn: 1178.1000 - fp: 831.3500 - loss: 0.2369 - prc: 0.9720 - precision: 0.9173 - recall: 0.8896 - tn: 9992.1504 - tp: 9502.4004"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0721 - accuracy: 0.9058 - auc: 0.9645 - cross entropy: 0.2364 - fn: 1347.9131 - fp: 946.5652 - loss: 0.2364 - prc: 0.9722 - precision: 0.9177 - recall: 0.8896 - tn: 11415.1738 - tp: 10866.3477"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0719 - accuracy: 0.9060 - auc: 0.9646 - cross entropy: 0.2360 - fn: 1516.8462 - fp: 1059.9615 - loss: 0.2360 - prc: 0.9723 - precision: 0.9182 - recall: 0.8896 - tn: 12837.3457 - tp: 12233.8457"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 28/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0718 - accuracy: 0.9061 - auc: 0.9647 - cross entropy: 0.2358 - fn: 1628.3928 - fp: 1134.7858 - loss: 0.2358 - prc: 0.9723 - precision: 0.9185 - recall: 0.8897 - tn: 13787.1074 - tp: 13145.7139"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 31/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0717 - accuracy: 0.9063 - auc: 0.9648 - cross entropy: 0.2355 - fn: 1797.0322 - fp: 1246.9354 - loss: 0.2355 - prc: 0.9724 - precision: 0.9189 - recall: 0.8897 - tn: 15212.2578 - tp: 14511.7744"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 34/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 21ms/step - Brier score: 0.0716 - accuracy: 0.9064 - auc: 0.9648 - cross entropy: 0.2352 - fn: 1967.5588 - fp: 1358.6471 - loss: 0.2352 - prc: 0.9724 - precision: 0.9192 - recall: 0.8897 - tn: 16641.5293 - tp: 15872.2646"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 37/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 21ms/step - Brier score: 0.0715 - accuracy: 0.9065 - auc: 0.9649 - cross entropy: 0.2350 - fn: 2137.9460 - fp: 1470.7838 - loss: 0.2350 - prc: 0.9725 - precision: 0.9195 - recall: 0.8896 - tn: 18068.5137 - tp: 17234.7559"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 40/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 21ms/step - Brier score: 0.0715 - accuracy: 0.9066 - auc: 0.9649 - cross entropy: 0.2348 - fn: 2308.3750 - fp: 1582.6250 - loss: 0.2348 - prc: 0.9725 - precision: 0.9197 - recall: 0.8896 - tn: 19493.5742 - tp: 18599.4258"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 43/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 21ms/step - Brier score: 0.0714 - accuracy: 0.9067 - auc: 0.9650 - cross entropy: 0.2346 - fn: 2478.1860 - fp: 1692.4419 - loss: 0.2346 - prc: 0.9725 - precision: 0.9200 - recall: 0.8896 - tn: 20918.9531 - tp: 19966.4180"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 46/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0713 - accuracy: 0.9068 - auc: 0.9651 - cross entropy: 0.2344 - fn: 2647.4565 - fp: 1801.3260 - loss: 0.2344 - prc: 0.9726 - precision: 0.9203 - recall: 0.8896 - tn: 22346.4785 - tp: 21332.7383"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 49/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0712 - accuracy: 0.9069 - auc: 0.9651 - cross entropy: 0.2342 - fn: 2816.4490 - fp: 1910.6123 - loss: 0.2342 - prc: 0.9726 - precision: 0.9205 - recall: 0.8896 - tn: 23772.3887 - tp: 22700.5508"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 52/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0712 - accuracy: 0.9070 - auc: 0.9652 - cross entropy: 0.2340 - fn: 2985.1155 - fp: 2018.8077 - loss: 0.2340 - prc: 0.9727 - precision: 0.9207 - recall: 0.8896 - tn: 25196.9238 - tp: 24071.1543"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 54/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0711 - accuracy: 0.9071 - auc: 0.9652 - cross entropy: 0.2338 - fn: 3097.1667 - fp: 2090.0740 - loss: 0.2338 - prc: 0.9727 - precision: 0.9209 - recall: 0.8897 - tn: 26145.8887 - tp: 24986.8711"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 57/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0710 - accuracy: 0.9072 - auc: 0.9652 - cross entropy: 0.2336 - fn: 3265.3333 - fp: 2196.1228 - loss: 0.2336 - prc: 0.9727 - precision: 0.9211 - recall: 0.8897 - tn: 27568.8945 - tp: 26361.6484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 60/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0710 - accuracy: 0.9073 - auc: 0.9653 - cross entropy: 0.2334 - fn: 3433.1333 - fp: 2300.9167 - loss: 0.2334 - prc: 0.9728 - precision: 0.9214 - recall: 0.8897 - tn: 28994.5508 - tp: 27735.4004"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 63/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0709 - accuracy: 0.9075 - auc: 0.9654 - cross entropy: 0.2331 - fn: 3600.1587 - fp: 2404.9841 - loss: 0.2331 - prc: 0.9728 - precision: 0.9216 - recall: 0.8898 - tn: 30421.8730 - tp: 29108.9844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 66/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0708 - accuracy: 0.9076 - auc: 0.9654 - cross entropy: 0.2329 - fn: 3766.6667 - fp: 2509.0454 - loss: 0.2329 - prc: 0.9729 - precision: 0.9219 - recall: 0.8898 - tn: 31848.6055 - tp: 30483.6816"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 69/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0707 - accuracy: 0.9077 - auc: 0.9655 - cross entropy: 0.2326 - fn: 3932.7102 - fp: 2612.7681 - loss: 0.2326 - prc: 0.9730 - precision: 0.9221 - recall: 0.8899 - tn: 33277.2734 - tp: 31857.2461"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 72/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0706 - accuracy: 0.9078 - auc: 0.9656 - cross entropy: 0.2324 - fn: 4098.8613 - fp: 2715.6667 - loss: 0.2324 - prc: 0.9730 - precision: 0.9223 - recall: 0.8900 - tn: 34708.5273 - tp: 33228.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 75/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0705 - accuracy: 0.9079 - auc: 0.9656 - cross entropy: 0.2321 - fn: 4265.2266 - fp: 2818.2932 - loss: 0.2321 - prc: 0.9730 - precision: 0.9225 - recall: 0.8900 - tn: 36139.2266 - tp: 34601.2539"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 78/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0705 - accuracy: 0.9081 - auc: 0.9657 - cross entropy: 0.2319 - fn: 4431.5771 - fp: 2919.8718 - loss: 0.2319 - prc: 0.9731 - precision: 0.9227 - recall: 0.8900 - tn: 37571.2188 - tp: 35973.3320"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 81/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0704 - accuracy: 0.9082 - auc: 0.9658 - cross entropy: 0.2316 - fn: 4597.4321 - fp: 3020.7285 - loss: 0.2316 - prc: 0.9731 - precision: 0.9229 - recall: 0.8901 - tn: 39004.5195 - tp: 37345.3203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 84/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0703 - accuracy: 0.9083 - auc: 0.9658 - cross entropy: 0.2313 - fn: 4762.5835 - fp: 3121.2500 - loss: 0.2313 - prc: 0.9732 - precision: 0.9231 - recall: 0.8901 - tn: 40438.7383 - tp: 38717.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 87/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0702 - accuracy: 0.9084 - auc: 0.9659 - cross entropy: 0.2311 - fn: 4927.5400 - fp: 3221.8965 - loss: 0.2311 - prc: 0.9732 - precision: 0.9233 - recall: 0.8902 - tn: 41872.2539 - tp: 40090.3086"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 90/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0701 - accuracy: 0.9085 - auc: 0.9660 - cross entropy: 0.2309 - fn: 5092.5889 - fp: 3321.7888 - loss: 0.2309 - prc: 0.9733 - precision: 0.9235 - recall: 0.8902 - tn: 43306.6445 - tp: 41462.9766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 93/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0700 - accuracy: 0.9086 - auc: 0.9660 - cross entropy: 0.2306 - fn: 5256.8496 - fp: 3421.2151 - loss: 0.2306 - prc: 0.9733 - precision: 0.9237 - recall: 0.8903 - tn: 44744.3672 - tp: 42833.5703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 96/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0700 - accuracy: 0.9087 - auc: 0.9661 - cross entropy: 0.2304 - fn: 5420.2290 - fp: 3520.4895 - loss: 0.2304 - prc: 0.9734 - precision: 0.9239 - recall: 0.8903 - tn: 46183.1562 - tp: 44204.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 99/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0699 - accuracy: 0.9088 - auc: 0.9662 - cross entropy: 0.2301 - fn: 5583.0908 - fp: 3619.4749 - loss: 0.2301 - prc: 0.9734 - precision: 0.9240 - recall: 0.8904 - tn: 47623.4258 - tp: 45574.0117"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m102/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0698 - accuracy: 0.9090 - auc: 0.9662 - cross entropy: 0.2299 - fn: 5745.6079 - fp: 3717.8530 - loss: 0.2299 - prc: 0.9735 - precision: 0.9242 - recall: 0.8905 - tn: 49062.9492 - tp: 46945.5898"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m105/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0697 - accuracy: 0.9091 - auc: 0.9663 - cross entropy: 0.2296 - fn: 5907.8569 - fp: 3815.6953 - loss: 0.2296 - prc: 0.9735 - precision: 0.9244 - recall: 0.8905 - tn: 50502.0938 - tp: 48318.3516"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m108/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0696 - accuracy: 0.9092 - auc: 0.9663 - cross entropy: 0.2294 - fn: 6069.8613 - fp: 3913.4629 - loss: 0.2294 - prc: 0.9736 - precision: 0.9245 - recall: 0.8906 - tn: 51941.5820 - tp: 49691.0938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m111/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0696 - accuracy: 0.9093 - auc: 0.9664 - cross entropy: 0.2292 - fn: 6231.2163 - fp: 4010.6306 - loss: 0.2292 - prc: 0.9736 - precision: 0.9247 - recall: 0.8906 - tn: 53382.8359 - tp: 51063.3164"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m114/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0695 - accuracy: 0.9094 - auc: 0.9665 - cross entropy: 0.2289 - fn: 6391.9648 - fp: 4107.1665 - loss: 0.2289 - prc: 0.9736 - precision: 0.9248 - recall: 0.8907 - tn: 54825.4141 - tp: 52435.4570"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m117/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0694 - accuracy: 0.9095 - auc: 0.9665 - cross entropy: 0.2287 - fn: 6552.5127 - fp: 4203.3760 - loss: 0.2287 - prc: 0.9737 - precision: 0.9250 - recall: 0.8908 - tn: 56269.0430 - tp: 53807.0703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m120/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0693 - accuracy: 0.9096 - auc: 0.9666 - cross entropy: 0.2284 - fn: 6712.6919 - fp: 4299.6919 - loss: 0.2284 - prc: 0.9737 - precision: 0.9251 - recall: 0.8908 - tn: 57711.5156 - tp: 55180.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m123/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0692 - accuracy: 0.9097 - auc: 0.9667 - cross entropy: 0.2282 - fn: 6872.8535 - fp: 4395.7559 - loss: 0.2282 - prc: 0.9738 - precision: 0.9253 - recall: 0.8909 - tn: 59153.9609 - tp: 56553.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m126/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0692 - accuracy: 0.9098 - auc: 0.9667 - cross entropy: 0.2280 - fn: 7032.7539 - fp: 4491.1348 - loss: 0.2280 - prc: 0.9738 - precision: 0.9254 - recall: 0.8910 - tn: 60597.7695 - tp: 57926.3398"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m129/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0691 - accuracy: 0.9099 - auc: 0.9668 - cross entropy: 0.2278 - fn: 7192.1782 - fp: 4586.3257 - loss: 0.2278 - prc: 0.9739 - precision: 0.9256 - recall: 0.8910 - tn: 62043.0938 - tp: 59298.4023"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m132/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0690 - accuracy: 0.9100 - auc: 0.9669 - cross entropy: 0.2275 - fn: 7351.3940 - fp: 4681.0078 - loss: 0.2275 - prc: 0.9739 - precision: 0.9257 - recall: 0.8911 - tn: 63489.2344 - tp: 60670.3633"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m135/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 21ms/step - Brier score: 0.0689 - accuracy: 0.9101 - auc: 0.9669 - cross entropy: 0.2273 - fn: 7510.2148 - fp: 4775.4888 - loss: 0.2273 - prc: 0.9739 - precision: 0.9259 - recall: 0.8912 - tn: 64936.7344 - tp: 62041.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m138/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 21ms/step - Brier score: 0.0689 - accuracy: 0.9102 - auc: 0.9670 - cross entropy: 0.2271 - fn: 7668.8843 - fp: 4869.8696 - loss: 0.2271 - prc: 0.9740 - precision: 0.9260 - recall: 0.8912 - tn: 66384.7969 - tp: 63412.4492"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m141/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0688 - accuracy: 0.9103 - auc: 0.9670 - cross entropy: 0.2268 - fn: 7827.1489 - fp: 4963.6382 - loss: 0.2268 - prc: 0.9740 - precision: 0.9261 - recall: 0.8913 - tn: 67834.2031 - tp: 64783.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m144/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 21ms/step - Brier score: 0.0687 - accuracy: 0.9104 - auc: 0.9671 - cross entropy: 0.2266 - fn: 7985.1182 - fp: 5057.1665 - loss: 0.2266 - prc: 0.9741 - precision: 0.9263 - recall: 0.8914 - tn: 69283.5156 - tp: 66154.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m147/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0686 - accuracy: 0.9105 - auc: 0.9672 - cross entropy: 0.2264 - fn: 8142.8232 - fp: 5150.3062 - loss: 0.2264 - prc: 0.9741 - precision: 0.9264 - recall: 0.8914 - tn: 70733.1406 - tp: 67525.7266"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m150/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0686 - accuracy: 0.9106 - auc: 0.9672 - cross entropy: 0.2262 - fn: 8300.4336 - fp: 5242.9531 - loss: 0.2262 - prc: 0.9741 - precision: 0.9265 - recall: 0.8915 - tn: 72183.7031 - tp: 68896.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m153/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0685 - accuracy: 0.9107 - auc: 0.9673 - cross entropy: 0.2260 - fn: 8457.6475 - fp: 5335.2026 - loss: 0.2260 - prc: 0.9742 - precision: 0.9267 - recall: 0.8916 - tn: 73634.8672 - tp: 70268.2812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m156/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0684 - accuracy: 0.9108 - auc: 0.9673 - cross entropy: 0.2257 - fn: 8614.4229 - fp: 5427.0322 - loss: 0.2257 - prc: 0.9742 - precision: 0.9268 - recall: 0.8916 - tn: 75087.3047 - tp: 71639.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m159/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0684 - accuracy: 0.9109 - auc: 0.9674 - cross entropy: 0.2255 - fn: 8770.8115 - fp: 5518.5347 - loss: 0.2255 - prc: 0.9743 - precision: 0.9269 - recall: 0.8917 - tn: 76540.2109 - tp: 73010.4453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m162/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0683 - accuracy: 0.9110 - auc: 0.9674 - cross entropy: 0.2253 - fn: 8926.9316 - fp: 5609.6543 - loss: 0.2253 - prc: 0.9743 - precision: 0.9270 - recall: 0.8918 - tn: 77993.3047 - tp: 74382.1094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m165/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0682 - accuracy: 0.9111 - auc: 0.9675 - cross entropy: 0.2251 - fn: 9082.8125 - fp: 5700.4062 - loss: 0.2251 - prc: 0.9743 - precision: 0.9272 - recall: 0.8918 - tn: 79447.3359 - tp: 75753.4453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m168/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0681 - accuracy: 0.9112 - auc: 0.9676 - cross entropy: 0.2249 - fn: 9238.2324 - fp: 5790.5415 - loss: 0.2249 - prc: 0.9744 - precision: 0.9273 - recall: 0.8919 - tn: 80902.2969 - tp: 77124.9297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m171/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0681 - accuracy: 0.9113 - auc: 0.9676 - cross entropy: 0.2247 - fn: 9393.3037 - fp: 5880.3975 - loss: 0.2247 - prc: 0.9744 - precision: 0.9274 - recall: 0.8920 - tn: 82357.3906 - tp: 78496.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m174/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0680 - accuracy: 0.9114 - auc: 0.9677 - cross entropy: 0.2244 - fn: 9548.1318 - fp: 5969.9194 - loss: 0.2244 - prc: 0.9745 - precision: 0.9275 - recall: 0.8920 - tn: 83811.5938 - tp: 79870.3594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m177/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0679 - accuracy: 0.9115 - auc: 0.9677 - cross entropy: 0.2242 - fn: 9702.7910 - fp: 6058.8530 - loss: 0.2242 - prc: 0.9745 - precision: 0.9277 - recall: 0.8921 - tn: 85264.5625 - tp: 81245.7891"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m180/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0679 - accuracy: 0.9116 - auc: 0.9678 - cross entropy: 0.2240 - fn: 9857.0889 - fp: 6147.1279 - loss: 0.2240 - prc: 0.9745 - precision: 0.9278 - recall: 0.8922 - tn: 86717.8203 - tp: 82621.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m183/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0678 - accuracy: 0.9117 - auc: 0.9678 - cross entropy: 0.2238 - fn: 10011.0381 - fp: 6234.9946 - loss: 0.2238 - prc: 0.9746 - precision: 0.9279 - recall: 0.8922 - tn: 88171.7891 - tp: 83998.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m186/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0677 - accuracy: 0.9118 - auc: 0.9679 - cross entropy: 0.2236 - fn: 10164.6562 - fp: 6322.5107 - loss: 0.2236 - prc: 0.9746 - precision: 0.9280 - recall: 0.8923 - tn: 89625.8047 - tp: 85375.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m189/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0676 - accuracy: 0.9119 - auc: 0.9680 - cross entropy: 0.2234 - fn: 10317.9785 - fp: 6409.6880 - loss: 0.2234 - prc: 0.9747 - precision: 0.9282 - recall: 0.8924 - tn: 91080.2578 - tp: 86752.0703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m192/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0676 - accuracy: 0.9120 - auc: 0.9680 - cross entropy: 0.2232 - fn: 10470.8750 - fp: 6496.6821 - loss: 0.2232 - prc: 0.9747 - precision: 0.9283 - recall: 0.8925 - tn: 92535.0391 - tp: 88129.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m195/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0675 - accuracy: 0.9121 - auc: 0.9681 - cross entropy: 0.2230 - fn: 10623.4766 - fp: 6583.3438 - loss: 0.2230 - prc: 0.9747 - precision: 0.9284 - recall: 0.8925 - tn: 93989.6797 - tp: 89507.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m197/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0675 - accuracy: 0.9121 - auc: 0.9681 - cross entropy: 0.2228 - fn: 10725.2383 - fp: 6640.8579 - loss: 0.2228 - prc: 0.9748 - precision: 0.9285 - recall: 0.8926 - tn: 94959.5391 - tp: 90426.3672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m200/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0674 - accuracy: 0.9122 - auc: 0.9682 - cross entropy: 0.2226 - fn: 10877.5996 - fp: 6726.9702 - loss: 0.2226 - prc: 0.9748 - precision: 0.9286 - recall: 0.8926 - tn: 96415.0312 - tp: 91804.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m203/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0673 - accuracy: 0.9123 - auc: 0.9682 - cross entropy: 0.2224 - fn: 11029.7979 - fp: 6812.7388 - loss: 0.2224 - prc: 0.9748 - precision: 0.9287 - recall: 0.8927 - tn: 97870.6328 - tp: 93182.8359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m206/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0673 - accuracy: 0.9124 - auc: 0.9683 - cross entropy: 0.2222 - fn: 11181.5000 - fp: 6898.0532 - loss: 0.2222 - prc: 0.9749 - precision: 0.9288 - recall: 0.8928 - tn: 99327.2656 - tp: 94561.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m209/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0672 - accuracy: 0.9125 - auc: 0.9683 - cross entropy: 0.2220 - fn: 11332.9326 - fp: 6983.2295 - loss: 0.2220 - prc: 0.9749 - precision: 0.9290 - recall: 0.8929 - tn: 100784.5625 - tp: 95939.2734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m212/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0671 - accuracy: 0.9126 - auc: 0.9684 - cross entropy: 0.2218 - fn: 11484.2451 - fp: 7068.3301 - loss: 0.2218 - prc: 0.9749 - precision: 0.9291 - recall: 0.8929 - tn: 102241.6016 - tp: 97317.8281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m215/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0671 - accuracy: 0.9127 - auc: 0.9684 - cross entropy: 0.2216 - fn: 11635.3623 - fp: 7153.0557 - loss: 0.2216 - prc: 0.9750 - precision: 0.9292 - recall: 0.8930 - tn: 103699.1328 - tp: 98696.4531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m218/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0670 - accuracy: 0.9128 - auc: 0.9685 - cross entropy: 0.2214 - fn: 11786.2197 - fp: 7237.5596 - loss: 0.2214 - prc: 0.9750 - precision: 0.9293 - recall: 0.8931 - tn: 105157.2500 - tp: 100074.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m221/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0669 - accuracy: 0.9129 - auc: 0.9685 - cross entropy: 0.2212 - fn: 11936.6289 - fp: 7321.8418 - loss: 0.2212 - prc: 0.9751 - precision: 0.9294 - recall: 0.8931 - tn: 106615.1875 - tp: 101454.3438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m224/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0669 - accuracy: 0.9130 - auc: 0.9686 - cross entropy: 0.2210 - fn: 12086.9551 - fp: 7405.7856 - loss: 0.2210 - prc: 0.9751 - precision: 0.9295 - recall: 0.8932 - tn: 108073.7109 - tp: 102833.5469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m227/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0668 - accuracy: 0.9130 - auc: 0.9687 - cross entropy: 0.2208 - fn: 12237.1104 - fp: 7489.5376 - loss: 0.2208 - prc: 0.9751 - precision: 0.9296 - recall: 0.8933 - tn: 109532.6406 - tp: 104212.7109"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m230/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0667 - accuracy: 0.9131 - auc: 0.9687 - cross entropy: 0.2206 - fn: 12387.0352 - fp: 7572.9307 - loss: 0.2206 - prc: 0.9752 - precision: 0.9297 - recall: 0.8933 - tn: 110992.0938 - tp: 105591.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m233/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0667 - accuracy: 0.9132 - auc: 0.9688 - cross entropy: 0.2204 - fn: 12536.7725 - fp: 7656.0903 - loss: 0.2204 - prc: 0.9752 - precision: 0.9298 - recall: 0.8934 - tn: 112451.1328 - tp: 106972.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m236/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0666 - accuracy: 0.9133 - auc: 0.9688 - cross entropy: 0.2202 - fn: 12686.5674 - fp: 7738.8516 - loss: 0.2202 - prc: 0.9752 - precision: 0.9299 - recall: 0.8935 - tn: 113909.5547 - tp: 108353.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m239/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0665 - accuracy: 0.9134 - auc: 0.9689 - cross entropy: 0.2200 - fn: 12836.4229 - fp: 7821.2847 - loss: 0.2200 - prc: 0.9753 - precision: 0.9301 - recall: 0.8935 - tn: 115367.2500 - tp: 109735.0391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m242/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0665 - accuracy: 0.9135 - auc: 0.9689 - cross entropy: 0.2198 - fn: 12985.9961 - fp: 7903.6035 - loss: 0.2198 - prc: 0.9753 - precision: 0.9302 - recall: 0.8936 - tn: 116825.4531 - tp: 111116.9531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m245/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0664 - accuracy: 0.9136 - auc: 0.9690 - cross entropy: 0.2196 - fn: 13135.4160 - fp: 7985.6655 - loss: 0.2196 - prc: 0.9754 - precision: 0.9303 - recall: 0.8937 - tn: 118283.3047 - tp: 112499.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m248/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0663 - accuracy: 0.9136 - auc: 0.9690 - cross entropy: 0.2194 - fn: 13284.5723 - fp: 8067.4478 - loss: 0.2194 - prc: 0.9754 - precision: 0.9304 - recall: 0.8937 - tn: 119741.8047 - tp: 113882.1719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m251/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0663 - accuracy: 0.9137 - auc: 0.9691 - cross entropy: 0.2192 - fn: 13433.5654 - fp: 8149.3428 - loss: 0.2192 - prc: 0.9754 - precision: 0.9305 - recall: 0.8938 - tn: 121200.5547 - tp: 115264.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m254/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0662 - accuracy: 0.9138 - auc: 0.9691 - cross entropy: 0.2190 - fn: 13582.4365 - fp: 8231.0000 - loss: 0.2190 - prc: 0.9755 - precision: 0.9306 - recall: 0.8939 - tn: 122659.3203 - tp: 116647.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m257/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0662 - accuracy: 0.9139 - auc: 0.9692 - cross entropy: 0.2188 - fn: 13731.0312 - fp: 8312.1865 - loss: 0.2188 - prc: 0.9755 - precision: 0.9307 - recall: 0.8939 - tn: 124118.6797 - tp: 118030.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m260/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0661 - accuracy: 0.9140 - auc: 0.9692 - cross entropy: 0.2186 - fn: 13879.5273 - fp: 8392.9424 - loss: 0.2186 - prc: 0.9755 - precision: 0.9308 - recall: 0.8940 - tn: 125578.2969 - tp: 119413.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m263/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0660 - accuracy: 0.9141 - auc: 0.9693 - cross entropy: 0.2184 - fn: 14027.8818 - fp: 8473.2549 - loss: 0.2184 - prc: 0.9756 - precision: 0.9309 - recall: 0.8940 - tn: 127037.9531 - tp: 120796.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m266/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0660 - accuracy: 0.9141 - auc: 0.9693 - cross entropy: 0.2182 - fn: 14175.8877 - fp: 8553.2559 - loss: 0.2182 - prc: 0.9756 - precision: 0.9310 - recall: 0.8941 - tn: 128497.8984 - tp: 122180.9531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m269/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0659 - accuracy: 0.9142 - auc: 0.9694 - cross entropy: 0.2180 - fn: 14323.5615 - fp: 8633.1299 - loss: 0.2180 - prc: 0.9756 - precision: 0.9311 - recall: 0.8942 - tn: 129958.1641 - tp: 123565.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m272/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0658 - accuracy: 0.9143 - auc: 0.9694 - cross entropy: 0.2178 - fn: 14471.1504 - fp: 8712.8525 - loss: 0.2178 - prc: 0.9757 - precision: 0.9312 - recall: 0.8942 - tn: 131418.8281 - tp: 124949.1719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m275/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0658 - accuracy: 0.9144 - auc: 0.9695 - cross entropy: 0.2176 - fn: 14618.6250 - fp: 8792.3525 - loss: 0.2176 - prc: 0.9757 - precision: 0.9313 - recall: 0.8943 - tn: 132879.4844 - tp: 126333.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0657 - accuracy: 0.9145 - auc: 0.9695 - cross entropy: 0.2174 - fn: 14765.8311 - fp: 8871.4746 - loss: 0.2174 - prc: 0.9757 - precision: 0.9314 - recall: 0.8944 - tn: 134340.9219 - tp: 127717.7656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 20ms/step - Brier score: 0.0657 - accuracy: 0.9145 - auc: 0.9696 - cross entropy: 0.2174 - fn: 14814.5234 - fp: 8897.6309 - loss: 0.2174 - prc: 0.9758 - precision: 0.9314 - recall: 0.8944 - tn: 134824.6719 - tp: 128175.8359 - val_Brier score: 0.0228 - val_accuracy: 0.9804 - val_auc: 0.9865 - val_cross entropy: 0.1128 - val_fn: 5.0000 - val_fp: 889.0000 - val_loss: 0.1128 - val_prc: 0.7845 - val_precision: 0.0797 - val_recall: 0.9390 - val_tn: 44598.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0507 - accuracy: 0.9360 - auc: 0.9814 - cross entropy: 0.1792 - fn: 88.0000 - fp: 43.0000 - loss: 0.1792 - prc: 0.9831 - precision: 0.9563 - recall: 0.9145 - tn: 976.0000 - tp: 941.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 14ms/step - Brier score: 0.0523 - accuracy: 0.9303 - auc: 0.9809 - cross entropy: 0.1765 - fn: 287.4000 - fp: 146.6000 - loss: 0.1765 - prc: 0.9835 - precision: 0.9514 - recall: 0.9086 - tn: 2889.0000 - tp: 2821.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0523 - accuracy: 0.9303 - auc: 0.9809 - cross entropy: 0.1755 - fn: 424.7500 - fp: 220.6250 - loss: 0.1755 - prc: 0.9836 - precision: 0.9508 - recall: 0.9088 - tn: 4353.8750 - tp: 4216.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0522 - accuracy: 0.9306 - auc: 0.9808 - cross entropy: 0.1752 - fn: 565.1818 - fp: 288.7273 - loss: 0.1752 - prc: 0.9836 - precision: 0.9512 - recall: 0.9088 - tn: 5817.1816 - tp: 5616.9092"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0522 - accuracy: 0.9308 - auc: 0.9808 - cross entropy: 0.1749 - fn: 705.1429 - fp: 354.7143 - loss: 0.1749 - prc: 0.9837 - precision: 0.9516 - recall: 0.9088 - tn: 7278.1431 - tp: 7022.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0521 - accuracy: 0.9310 - auc: 0.9808 - cross entropy: 0.1747 - fn: 843.0000 - fp: 423.7647 - loss: 0.1747 - prc: 0.9837 - precision: 0.9518 - recall: 0.9090 - tn: 8737.3525 - tp: 8427.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0521 - accuracy: 0.9311 - auc: 0.9808 - cross entropy: 0.1746 - fn: 980.7000 - fp: 493.9500 - loss: 0.1746 - prc: 0.9837 - precision: 0.9519 - recall: 0.9091 - tn: 10205.2002 - tp: 9824.1504"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0521 - accuracy: 0.9313 - auc: 0.9808 - cross entropy: 0.1744 - fn: 1118.3043 - fp: 562.7391 - loss: 0.1744 - prc: 0.9837 - precision: 0.9520 - recall: 0.9092 - tn: 11672.0869 - tp: 11222.8691"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0520 - accuracy: 0.9314 - auc: 0.9808 - cross entropy: 0.1742 - fn: 1255.6154 - fp: 630.1539 - loss: 0.1742 - prc: 0.9838 - precision: 0.9521 - recall: 0.9093 - tn: 13139.7695 - tp: 12622.4619"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0520 - accuracy: 0.9315 - auc: 0.9808 - cross entropy: 0.1741 - fn: 1394.0690 - fp: 697.6552 - loss: 0.1741 - prc: 0.9838 - precision: 0.9522 - recall: 0.9093 - tn: 14610.5176 - tp: 14017.7588"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0519 - accuracy: 0.9316 - auc: 0.9809 - cross entropy: 0.1739 - fn: 1531.5938 - fp: 765.0312 - loss: 0.1739 - prc: 0.9838 - precision: 0.9523 - recall: 0.9094 - tn: 16081.5000 - tp: 15413.8750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0519 - accuracy: 0.9317 - auc: 0.9809 - cross entropy: 0.1738 - fn: 1667.8000 - fp: 831.1429 - loss: 0.1738 - prc: 0.9838 - precision: 0.9524 - recall: 0.9095 - tn: 17548.5723 - tp: 16816.4863"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0518 - accuracy: 0.9319 - auc: 0.9809 - cross entropy: 0.1736 - fn: 1803.5000 - fp: 897.4211 - loss: 0.1736 - prc: 0.9839 - precision: 0.9526 - recall: 0.9096 - tn: 19015.4746 - tp: 18219.6055"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0518 - accuracy: 0.9320 - auc: 0.9809 - cross entropy: 0.1733 - fn: 1937.7073 - fp: 962.9512 - loss: 0.1733 - prc: 0.9839 - precision: 0.9527 - recall: 0.9097 - tn: 20487.1211 - tp: 19620.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0517 - accuracy: 0.9321 - auc: 0.9810 - cross entropy: 0.1731 - fn: 2071.2046 - fp: 1029.3409 - loss: 0.1731 - prc: 0.9839 - precision: 0.9528 - recall: 0.9098 - tn: 21960.8867 - tp: 21018.5684"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0517 - accuracy: 0.9322 - auc: 0.9810 - cross entropy: 0.1730 - fn: 2204.0425 - fp: 1096.7234 - loss: 0.1730 - prc: 0.9839 - precision: 0.9528 - recall: 0.9100 - tn: 23433.8730 - tp: 22417.3613"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0516 - accuracy: 0.9323 - auc: 0.9810 - cross entropy: 0.1728 - fn: 2336.8799 - fp: 1164.2800 - loss: 0.1728 - prc: 0.9840 - precision: 0.9529 - recall: 0.9101 - tn: 24906.0801 - tp: 23816.7598"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0516 - accuracy: 0.9324 - auc: 0.9811 - cross entropy: 0.1726 - fn: 2470.2642 - fp: 1231.3396 - loss: 0.1726 - prc: 0.9840 - precision: 0.9529 - recall: 0.9102 - tn: 26376.1895 - tp: 25218.2070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0515 - accuracy: 0.9325 - auc: 0.9811 - cross entropy: 0.1725 - fn: 2603.5894 - fp: 1298.6072 - loss: 0.1725 - prc: 0.9840 - precision: 0.9530 - recall: 0.9103 - tn: 27845.4473 - tp: 26620.3574"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0515 - accuracy: 0.9326 - auc: 0.9811 - cross entropy: 0.1723 - fn: 2735.3052 - fp: 1366.1356 - loss: 0.1723 - prc: 0.9840 - precision: 0.9530 - recall: 0.9104 - tn: 29318.7285 - tp: 28019.8301"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0514 - accuracy: 0.9327 - auc: 0.9812 - cross entropy: 0.1721 - fn: 2867.0322 - fp: 1433.9517 - loss: 0.1721 - prc: 0.9841 - precision: 0.9530 - recall: 0.9105 - tn: 30793.9355 - tp: 29417.0801"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0514 - accuracy: 0.9327 - auc: 0.9812 - cross entropy: 0.1720 - fn: 2998.4922 - fp: 1501.7230 - loss: 0.1720 - prc: 0.9841 - precision: 0.9531 - recall: 0.9106 - tn: 32268.6777 - tp: 30815.1074"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0513 - accuracy: 0.9328 - auc: 0.9812 - cross entropy: 0.1718 - fn: 3129.1177 - fp: 1568.9706 - loss: 0.1718 - prc: 0.9841 - precision: 0.9531 - recall: 0.9107 - tn: 33746.3516 - tp: 32211.5586"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0513 - accuracy: 0.9329 - auc: 0.9813 - cross entropy: 0.1717 - fn: 3259.3804 - fp: 1635.7183 - loss: 0.1717 - prc: 0.9841 - precision: 0.9531 - recall: 0.9108 - tn: 35222.1680 - tp: 33610.7305"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0513 - accuracy: 0.9330 - auc: 0.9813 - cross entropy: 0.1715 - fn: 3389.1758 - fp: 1702.2703 - loss: 0.1715 - prc: 0.9842 - precision: 0.9532 - recall: 0.9109 - tn: 36698.5391 - tp: 35010.0117"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 77/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0512 - accuracy: 0.9330 - auc: 0.9813 - cross entropy: 0.1714 - fn: 3518.5715 - fp: 1768.5195 - loss: 0.1714 - prc: 0.9842 - precision: 0.9532 - recall: 0.9110 - tn: 38176.4297 - tp: 36408.4805"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 80/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0512 - accuracy: 0.9331 - auc: 0.9814 - cross entropy: 0.1712 - fn: 3647.8750 - fp: 1835.0625 - loss: 0.1712 - prc: 0.9842 - precision: 0.9533 - recall: 0.9111 - tn: 39652.5000 - tp: 37808.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 83/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0511 - accuracy: 0.9332 - auc: 0.9814 - cross entropy: 0.1710 - fn: 3777.5542 - fp: 1901.2531 - loss: 0.1710 - prc: 0.9842 - precision: 0.9533 - recall: 0.9112 - tn: 41127.4805 - tp: 39209.7109"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 86/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0511 - accuracy: 0.9333 - auc: 0.9814 - cross entropy: 0.1709 - fn: 3907.2673 - fp: 1966.6163 - loss: 0.1709 - prc: 0.9843 - precision: 0.9533 - recall: 0.9113 - tn: 42602.3242 - tp: 40611.7891"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 89/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0510 - accuracy: 0.9333 - auc: 0.9815 - cross entropy: 0.1707 - fn: 4037.0562 - fp: 2032.2247 - loss: 0.1707 - prc: 0.9843 - precision: 0.9534 - recall: 0.9114 - tn: 44076.5859 - tp: 42014.1367"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 92/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0510 - accuracy: 0.9334 - auc: 0.9815 - cross entropy: 0.1706 - fn: 4166.5107 - fp: 2097.6196 - loss: 0.1706 - prc: 0.9843 - precision: 0.9534 - recall: 0.9115 - tn: 45548.2188 - tp: 43419.6523"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 95/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0509 - accuracy: 0.9335 - auc: 0.9815 - cross entropy: 0.1705 - fn: 4296.3789 - fp: 2163.0947 - loss: 0.1705 - prc: 0.9843 - precision: 0.9535 - recall: 0.9115 - tn: 47019.7773 - tp: 44824.7461"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 98/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0509 - accuracy: 0.9335 - auc: 0.9816 - cross entropy: 0.1703 - fn: 4426.0410 - fp: 2228.3367 - loss: 0.1703 - prc: 0.9843 - precision: 0.9535 - recall: 0.9116 - tn: 48491.2773 - tp: 46230.3477"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m101/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0509 - accuracy: 0.9336 - auc: 0.9816 - cross entropy: 0.1702 - fn: 4555.2476 - fp: 2293.1980 - loss: 0.1702 - prc: 0.9844 - precision: 0.9536 - recall: 0.9117 - tn: 49963.5938 - tp: 47635.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m104/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0508 - accuracy: 0.9336 - auc: 0.9816 - cross entropy: 0.1700 - fn: 4684.2500 - fp: 2357.9326 - loss: 0.1700 - prc: 0.9844 - precision: 0.9536 - recall: 0.9118 - tn: 51437.0000 - tp: 49040.8164"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m107/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0508 - accuracy: 0.9337 - auc: 0.9817 - cross entropy: 0.1699 - fn: 4813.5327 - fp: 2422.7290 - loss: 0.1699 - prc: 0.9844 - precision: 0.9536 - recall: 0.9118 - tn: 52910.3086 - tp: 50445.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m110/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0507 - accuracy: 0.9338 - auc: 0.9817 - cross entropy: 0.1698 - fn: 4942.9907 - fp: 2487.2910 - loss: 0.1698 - prc: 0.9844 - precision: 0.9537 - recall: 0.9119 - tn: 54383.1172 - tp: 51850.6016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m113/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0507 - accuracy: 0.9338 - auc: 0.9817 - cross entropy: 0.1696 - fn: 5072.3628 - fp: 2551.6726 - loss: 0.1696 - prc: 0.9845 - precision: 0.9537 - recall: 0.9120 - tn: 55855.9727 - tp: 53255.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m116/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0507 - accuracy: 0.9339 - auc: 0.9817 - cross entropy: 0.1695 - fn: 5201.5864 - fp: 2616.0776 - loss: 0.1695 - prc: 0.9845 - precision: 0.9538 - recall: 0.9120 - tn: 57329.7930 - tp: 54660.5430"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m119/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0506 - accuracy: 0.9339 - auc: 0.9818 - cross entropy: 0.1694 - fn: 5331.0503 - fp: 2680.4453 - loss: 0.1694 - prc: 0.9845 - precision: 0.9538 - recall: 0.9121 - tn: 58802.6055 - tp: 56065.8984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m122/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0506 - accuracy: 0.9340 - auc: 0.9818 - cross entropy: 0.1693 - fn: 5460.1885 - fp: 2744.1558 - loss: 0.1693 - prc: 0.9845 - precision: 0.9538 - recall: 0.9122 - tn: 60275.1484 - tp: 57472.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m125/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0506 - accuracy: 0.9340 - auc: 0.9818 - cross entropy: 0.1691 - fn: 5589.1279 - fp: 2807.9199 - loss: 0.1691 - prc: 0.9845 - precision: 0.9539 - recall: 0.9122 - tn: 61747.0781 - tp: 58879.8711"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m128/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0505 - accuracy: 0.9341 - auc: 0.9819 - cross entropy: 0.1690 - fn: 5717.7578 - fp: 2871.7734 - loss: 0.1690 - prc: 0.9846 - precision: 0.9539 - recall: 0.9123 - tn: 63219.9141 - tp: 60286.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m131/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0505 - accuracy: 0.9341 - auc: 0.9819 - cross entropy: 0.1689 - fn: 5846.0918 - fp: 2935.5344 - loss: 0.1689 - prc: 0.9846 - precision: 0.9540 - recall: 0.9123 - tn: 64691.9453 - tp: 61694.4258"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m133/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0505 - accuracy: 0.9341 - auc: 0.9819 - cross entropy: 0.1688 - fn: 5931.7368 - fp: 2977.9473 - loss: 0.1688 - prc: 0.9846 - precision: 0.9540 - recall: 0.9124 - tn: 65673.0859 - tp: 62633.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m136/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0504 - accuracy: 0.9342 - auc: 0.9819 - cross entropy: 0.1687 - fn: 6059.8530 - fp: 3041.7354 - loss: 0.1687 - prc: 0.9846 - precision: 0.9540 - recall: 0.9124 - tn: 67144.4297 - tp: 64041.9844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m139/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0504 - accuracy: 0.9342 - auc: 0.9819 - cross entropy: 0.1686 - fn: 6187.7192 - fp: 3105.4963 - loss: 0.1686 - prc: 0.9846 - precision: 0.9541 - recall: 0.9125 - tn: 68615.8438 - tp: 65450.9414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m142/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0504 - accuracy: 0.9343 - auc: 0.9820 - cross entropy: 0.1685 - fn: 6315.5493 - fp: 3168.9084 - loss: 0.1685 - prc: 0.9847 - precision: 0.9541 - recall: 0.9125 - tn: 70087.0312 - tp: 66860.5156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m145/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0503 - accuracy: 0.9343 - auc: 0.9820 - cross entropy: 0.1684 - fn: 6443.2070 - fp: 3232.2139 - loss: 0.1684 - prc: 0.9847 - precision: 0.9541 - recall: 0.9126 - tn: 71557.8984 - tp: 68270.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m148/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0503 - accuracy: 0.9344 - auc: 0.9820 - cross entropy: 0.1683 - fn: 6570.6353 - fp: 3295.5000 - loss: 0.1683 - prc: 0.9847 - precision: 0.9542 - recall: 0.9127 - tn: 73028.0078 - tp: 69681.8594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m151/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0503 - accuracy: 0.9344 - auc: 0.9820 - cross entropy: 0.1682 - fn: 6697.9468 - fp: 3359.0332 - loss: 0.1682 - prc: 0.9847 - precision: 0.9542 - recall: 0.9127 - tn: 74498.3672 - tp: 71092.6562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m154/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0502 - accuracy: 0.9345 - auc: 0.9821 - cross entropy: 0.1681 - fn: 6824.9287 - fp: 3422.4480 - loss: 0.1681 - prc: 0.9847 - precision: 0.9542 - recall: 0.9128 - tn: 75969.0469 - tp: 72503.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m157/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0502 - accuracy: 0.9345 - auc: 0.9821 - cross entropy: 0.1680 - fn: 6951.5732 - fp: 3486.0447 - loss: 0.1680 - prc: 0.9847 - precision: 0.9543 - recall: 0.9128 - tn: 77439.7109 - tp: 73914.6719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m160/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0502 - accuracy: 0.9346 - auc: 0.9821 - cross entropy: 0.1679 - fn: 7078.2500 - fp: 3549.6626 - loss: 0.1679 - prc: 0.9848 - precision: 0.9543 - recall: 0.9129 - tn: 78910.0625 - tp: 75326.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m163/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0501 - accuracy: 0.9346 - auc: 0.9821 - cross entropy: 0.1678 - fn: 7204.5522 - fp: 3613.0798 - loss: 0.1678 - prc: 0.9848 - precision: 0.9543 - recall: 0.9130 - tn: 80381.4688 - tp: 76736.8984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m166/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0501 - accuracy: 0.9346 - auc: 0.9822 - cross entropy: 0.1677 - fn: 7330.6265 - fp: 3676.2590 - loss: 0.1677 - prc: 0.9848 - precision: 0.9544 - recall: 0.9130 - tn: 81852.5000 - tp: 78148.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m169/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0501 - accuracy: 0.9347 - auc: 0.9822 - cross entropy: 0.1676 - fn: 7456.5859 - fp: 3739.1123 - loss: 0.1676 - prc: 0.9848 - precision: 0.9544 - recall: 0.9131 - tn: 83323.3281 - tp: 79560.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m172/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0501 - accuracy: 0.9347 - auc: 0.9822 - cross entropy: 0.1675 - fn: 7582.4766 - fp: 3801.7268 - loss: 0.1675 - prc: 0.9848 - precision: 0.9544 - recall: 0.9131 - tn: 84795.0234 - tp: 80972.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m175/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0500 - accuracy: 0.9348 - auc: 0.9822 - cross entropy: 0.1674 - fn: 7708.1943 - fp: 3864.5486 - loss: 0.1674 - prc: 0.9849 - precision: 0.9545 - recall: 0.9132 - tn: 86266.6172 - tp: 82384.6406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m178/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0500 - accuracy: 0.9348 - auc: 0.9823 - cross entropy: 0.1673 - fn: 7833.6797 - fp: 3927.4326 - loss: 0.1673 - prc: 0.9849 - precision: 0.9545 - recall: 0.9132 - tn: 87738.8516 - tp: 83796.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m181/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0500 - accuracy: 0.9349 - auc: 0.9823 - cross entropy: 0.1672 - fn: 7958.9004 - fp: 3990.0994 - loss: 0.1672 - prc: 0.9849 - precision: 0.9545 - recall: 0.9133 - tn: 89211.6641 - tp: 85207.3359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m184/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0499 - accuracy: 0.9349 - auc: 0.9823 - cross entropy: 0.1671 - fn: 8083.8530 - fp: 4052.7065 - loss: 0.1671 - prc: 0.9849 - precision: 0.9546 - recall: 0.9133 - tn: 90684.7422 - tp: 86618.6953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m187/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0499 - accuracy: 0.9349 - auc: 0.9823 - cross entropy: 0.1670 - fn: 8208.7539 - fp: 4115.1445 - loss: 0.1670 - prc: 0.9849 - precision: 0.9546 - recall: 0.9134 - tn: 92157.5078 - tp: 88030.5938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m190/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0499 - accuracy: 0.9350 - auc: 0.9823 - cross entropy: 0.1669 - fn: 8333.4365 - fp: 4177.5894 - loss: 0.1669 - prc: 0.9849 - precision: 0.9546 - recall: 0.9134 - tn: 93630.0234 - tp: 89442.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m193/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0498 - accuracy: 0.9350 - auc: 0.9824 - cross entropy: 0.1668 - fn: 8457.9482 - fp: 4239.8496 - loss: 0.1668 - prc: 0.9850 - precision: 0.9546 - recall: 0.9135 - tn: 95102.8125 - tp: 90855.3906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m196/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0498 - accuracy: 0.9351 - auc: 0.9824 - cross entropy: 0.1667 - fn: 8582.3008 - fp: 4302.0103 - loss: 0.1667 - prc: 0.9850 - precision: 0.9547 - recall: 0.9136 - tn: 96575.8750 - tp: 92267.8125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m199/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0498 - accuracy: 0.9351 - auc: 0.9824 - cross entropy: 0.1666 - fn: 8706.3418 - fp: 4363.9194 - loss: 0.1666 - prc: 0.9850 - precision: 0.9547 - recall: 0.9136 - tn: 98049.0391 - tp: 93680.7031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m202/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0498 - accuracy: 0.9351 - auc: 0.9824 - cross entropy: 0.1665 - fn: 8830.3857 - fp: 4425.6436 - loss: 0.1665 - prc: 0.9850 - precision: 0.9547 - recall: 0.9137 - tn: 99521.9375 - tp: 95094.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m205/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0497 - accuracy: 0.9352 - auc: 0.9825 - cross entropy: 0.1664 - fn: 8954.2734 - fp: 4487.3999 - loss: 0.1664 - prc: 0.9850 - precision: 0.9548 - recall: 0.9137 - tn: 100995.5703 - tp: 96506.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m208/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0497 - accuracy: 0.9352 - auc: 0.9825 - cross entropy: 0.1663 - fn: 9077.9521 - fp: 4549.0288 - loss: 0.1663 - prc: 0.9850 - precision: 0.9548 - recall: 0.9138 - tn: 102469.2500 - tp: 97919.7656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m211/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0497 - accuracy: 0.9353 - auc: 0.9825 - cross entropy: 0.1662 - fn: 9201.4980 - fp: 4610.4453 - loss: 0.1662 - prc: 0.9851 - precision: 0.9548 - recall: 0.9138 - tn: 103943.0156 - tp: 99333.0391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m214/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0496 - accuracy: 0.9353 - auc: 0.9825 - cross entropy: 0.1661 - fn: 9324.6729 - fp: 4672.0093 - loss: 0.1661 - prc: 0.9851 - precision: 0.9549 - recall: 0.9139 - tn: 105416.1719 - tp: 100747.1484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m217/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0496 - accuracy: 0.9353 - auc: 0.9825 - cross entropy: 0.1660 - fn: 9447.7188 - fp: 4733.6128 - loss: 0.1660 - prc: 0.9851 - precision: 0.9549 - recall: 0.9139 - tn: 106888.9766 - tp: 102161.6875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m220/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0496 - accuracy: 0.9354 - auc: 0.9826 - cross entropy: 0.1659 - fn: 9570.7773 - fp: 4795.1909 - loss: 0.1659 - prc: 0.9851 - precision: 0.9549 - recall: 0.9140 - tn: 108361.0000 - tp: 103577.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m223/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0496 - accuracy: 0.9354 - auc: 0.9826 - cross entropy: 0.1658 - fn: 9693.6318 - fp: 4856.6772 - loss: 0.1658 - prc: 0.9851 - precision: 0.9549 - recall: 0.9140 - tn: 109833.4688 - tp: 104992.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m226/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0495 - accuracy: 0.9355 - auc: 0.9826 - cross entropy: 0.1657 - fn: 9816.2080 - fp: 4918.2036 - loss: 0.1657 - prc: 0.9851 - precision: 0.9550 - recall: 0.9141 - tn: 111305.9609 - tp: 106407.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m229/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0495 - accuracy: 0.9355 - auc: 0.9826 - cross entropy: 0.1656 - fn: 9938.8037 - fp: 4979.6724 - loss: 0.1656 - prc: 0.9852 - precision: 0.9550 - recall: 0.9141 - tn: 112777.8281 - tp: 107823.6953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m232/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0495 - accuracy: 0.9355 - auc: 0.9826 - cross entropy: 0.1655 - fn: 10061.3447 - fp: 5041.0044 - loss: 0.1655 - prc: 0.9852 - precision: 0.9550 - recall: 0.9142 - tn: 114250.0312 - tp: 109239.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m235/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0494 - accuracy: 0.9356 - auc: 0.9827 - cross entropy: 0.1654 - fn: 10183.7188 - fp: 5102.1318 - loss: 0.1654 - prc: 0.9852 - precision: 0.9551 - recall: 0.9142 - tn: 115722.1484 - tp: 110656.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m238/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0494 - accuracy: 0.9356 - auc: 0.9827 - cross entropy: 0.1653 - fn: 10305.9541 - fp: 5163.0127 - loss: 0.1653 - prc: 0.9852 - precision: 0.9551 - recall: 0.9143 - tn: 117194.8516 - tp: 112072.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m241/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0494 - accuracy: 0.9356 - auc: 0.9827 - cross entropy: 0.1653 - fn: 10427.8799 - fp: 5223.7720 - loss: 0.1653 - prc: 0.9852 - precision: 0.9551 - recall: 0.9143 - tn: 118668.2500 - tp: 113488.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m244/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0494 - accuracy: 0.9357 - auc: 0.9827 - cross entropy: 0.1652 - fn: 10549.7627 - fp: 5284.4468 - loss: 0.1652 - prc: 0.9852 - precision: 0.9551 - recall: 0.9144 - tn: 120141.5625 - tp: 114904.2266"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m247/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0493 - accuracy: 0.9357 - auc: 0.9828 - cross entropy: 0.1651 - fn: 10671.2793 - fp: 5345.2671 - loss: 0.1651 - prc: 0.9853 - precision: 0.9552 - recall: 0.9144 - tn: 121614.7734 - tp: 116320.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m250/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0493 - accuracy: 0.9358 - auc: 0.9828 - cross entropy: 0.1650 - fn: 10792.6797 - fp: 5406.0000 - loss: 0.1650 - prc: 0.9853 - precision: 0.9552 - recall: 0.9145 - tn: 123088.2969 - tp: 117737.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m253/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0493 - accuracy: 0.9358 - auc: 0.9828 - cross entropy: 0.1649 - fn: 10914.0830 - fp: 5466.6719 - loss: 0.1649 - prc: 0.9853 - precision: 0.9552 - recall: 0.9145 - tn: 124560.9922 - tp: 119154.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m256/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0492 - accuracy: 0.9358 - auc: 0.9828 - cross entropy: 0.1648 - fn: 11035.1914 - fp: 5527.1328 - loss: 0.1648 - prc: 0.9853 - precision: 0.9553 - recall: 0.9146 - tn: 126033.9375 - tp: 120571.7344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m259/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0492 - accuracy: 0.9359 - auc: 0.9828 - cross entropy: 0.1647 - fn: 11156.0391 - fp: 5587.5249 - loss: 0.1647 - prc: 0.9853 - precision: 0.9553 - recall: 0.9146 - tn: 127507.0156 - tp: 121989.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m262/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0492 - accuracy: 0.9359 - auc: 0.9829 - cross entropy: 0.1646 - fn: 11276.5918 - fp: 5648.0269 - loss: 0.1646 - prc: 0.9853 - precision: 0.9553 - recall: 0.9147 - tn: 128980.5156 - tp: 123406.8594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m265/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0492 - accuracy: 0.9359 - auc: 0.9829 - cross entropy: 0.1645 - fn: 11396.7998 - fp: 5708.5020 - loss: 0.1645 - prc: 0.9853 - precision: 0.9553 - recall: 0.9147 - tn: 130454.7109 - tp: 124823.9844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m268/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0491 - accuracy: 0.9360 - auc: 0.9829 - cross entropy: 0.1645 - fn: 11516.8057 - fp: 5768.8994 - loss: 0.1645 - prc: 0.9854 - precision: 0.9554 - recall: 0.9148 - tn: 131929.0625 - tp: 126241.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m271/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0491 - accuracy: 0.9360 - auc: 0.9829 - cross entropy: 0.1644 - fn: 11636.6494 - fp: 5829.1548 - loss: 0.1644 - prc: 0.9854 - precision: 0.9554 - recall: 0.9148 - tn: 133403.7969 - tp: 127658.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m274/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0491 - accuracy: 0.9361 - auc: 0.9829 - cross entropy: 0.1643 - fn: 11756.3975 - fp: 5889.3394 - loss: 0.1643 - prc: 0.9854 - precision: 0.9554 - recall: 0.9149 - tn: 134878.4844 - tp: 129075.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m277/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0491 - accuracy: 0.9361 - auc: 0.9830 - cross entropy: 0.1642 - fn: 11876.0576 - fp: 5949.5923 - loss: 0.1642 - prc: 0.9854 - precision: 0.9554 - recall: 0.9149 - tn: 136352.9062 - tp: 130493.4375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0490 - accuracy: 0.9361 - auc: 0.9830 - cross entropy: 0.1641 - fn: 11955.5195 - fp: 5989.6235 - loss: 0.1641 - prc: 0.9854 - precision: 0.9555 - recall: 0.9149 - tn: 137332.3906 - tp: 131435.1250 - val_Brier score: 0.0187 - val_accuracy: 0.9810 - val_auc: 0.9886 - val_cross entropy: 0.0874 - val_fn: 5.0000 - val_fp: 859.0000 - val_loss: 0.0874 - val_prc: 0.7531 - val_precision: 0.0823 - val_recall: 0.9390 - val_tn: 44628.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0409 - accuracy: 0.9458 - auc: 0.9884 - cross entropy: 0.1371 - fn: 73.0000 - fp: 38.0000 - loss: 0.1371 - prc: 0.9906 - precision: 0.9629 - recall: 0.9311 - tn: 951.0000 - tp: 986.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 15ms/step - Brier score: 0.0420 - accuracy: 0.9433 - auc: 0.9881 - cross entropy: 0.1401 - fn: 235.4000 - fp: 114.8000 - loss: 0.1401 - prc: 0.9898 - precision: 0.9612 - recall: 0.9250 - tn: 2939.2000 - tp: 2854.6001"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0423 - accuracy: 0.9431 - auc: 0.9879 - cross entropy: 0.1408 - fn: 352.2500 - fp: 174.8750 - loss: 0.1408 - prc: 0.9896 - precision: 0.9608 - recall: 0.9245 - tn: 4420.5000 - tp: 4268.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0424 - accuracy: 0.9429 - auc: 0.9879 - cross entropy: 0.1413 - fn: 467.5454 - fp: 236.0909 - loss: 0.1413 - prc: 0.9894 - precision: 0.9605 - recall: 0.9244 - tn: 5898.7271 - tp: 5685.6362"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0424 - accuracy: 0.9430 - auc: 0.9878 - cross entropy: 0.1415 - fn: 581.4286 - fp: 295.0000 - loss: 0.1415 - prc: 0.9893 - precision: 0.9604 - recall: 0.9246 - tn: 7368.7856 - tp: 7114.7856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0423 - accuracy: 0.9431 - auc: 0.9878 - cross entropy: 0.1415 - fn: 695.4117 - fp: 351.7059 - loss: 0.1415 - prc: 0.9893 - precision: 0.9605 - recall: 0.9247 - tn: 8838.4707 - tp: 8546.4121"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0423 - accuracy: 0.9433 - auc: 0.9878 - cross entropy: 0.1414 - fn: 806.3000 - fp: 408.9500 - loss: 0.1414 - prc: 0.9893 - precision: 0.9606 - recall: 0.9250 - tn: 10309.6504 - tp: 9979.0996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0423 - accuracy: 0.9434 - auc: 0.9878 - cross entropy: 0.1414 - fn: 918.7826 - fp: 466.9131 - loss: 0.1414 - prc: 0.9893 - precision: 0.9606 - recall: 0.9252 - tn: 11781.7822 - tp: 11408.5215"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0423 - accuracy: 0.9435 - auc: 0.9878 - cross entropy: 0.1413 - fn: 1031.5000 - fp: 523.4615 - loss: 0.1413 - prc: 0.9893 - precision: 0.9607 - recall: 0.9253 - tn: 13249.9619 - tp: 12843.0771"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0423 - accuracy: 0.9436 - auc: 0.9878 - cross entropy: 0.1413 - fn: 1143.7587 - fp: 580.4828 - loss: 0.1413 - prc: 0.9893 - precision: 0.9608 - recall: 0.9254 - tn: 14719.2070 - tp: 14276.5518"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0423 - accuracy: 0.9437 - auc: 0.9878 - cross entropy: 0.1413 - fn: 1256.8125 - fp: 637.5938 - loss: 0.1413 - prc: 0.9893 - precision: 0.9608 - recall: 0.9255 - tn: 16183.1562 - tp: 15714.4375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0422 - accuracy: 0.9437 - auc: 0.9878 - cross entropy: 0.1413 - fn: 1369.0000 - fp: 695.1429 - loss: 0.1413 - prc: 0.9893 - precision: 0.9609 - recall: 0.9256 - tn: 17646.2852 - tp: 17153.5723"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0422 - accuracy: 0.9438 - auc: 0.9878 - cross entropy: 0.1413 - fn: 1480.7894 - fp: 753.1053 - loss: 0.1413 - prc: 0.9893 - precision: 0.9609 - recall: 0.9258 - tn: 19109.2109 - tp: 18592.8945"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0422 - accuracy: 0.9438 - auc: 0.9879 - cross entropy: 0.1413 - fn: 1592.2195 - fp: 810.3171 - loss: 0.1413 - prc: 0.9893 - precision: 0.9609 - recall: 0.9259 - tn: 20576.2930 - tp: 20029.1699"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0422 - accuracy: 0.9439 - auc: 0.9879 - cross entropy: 0.1413 - fn: 1704.4318 - fp: 866.5227 - loss: 0.1413 - prc: 0.9893 - precision: 0.9610 - recall: 0.9259 - tn: 22046.8867 - tp: 21462.1582"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0422 - accuracy: 0.9439 - auc: 0.9879 - cross entropy: 0.1412 - fn: 1816.2128 - fp: 922.8298 - loss: 0.1412 - prc: 0.9893 - precision: 0.9610 - recall: 0.9260 - tn: 23522.5742 - tp: 22890.3828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0421 - accuracy: 0.9440 - auc: 0.9879 - cross entropy: 0.1412 - fn: 1928.3000 - fp: 979.1600 - loss: 0.1412 - prc: 0.9893 - precision: 0.9611 - recall: 0.9260 - tn: 24995.9805 - tp: 24320.5605"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0421 - accuracy: 0.9440 - auc: 0.9879 - cross entropy: 0.1412 - fn: 2040.3773 - fp: 1035.5094 - loss: 0.1412 - prc: 0.9893 - precision: 0.9611 - recall: 0.9261 - tn: 26469.3770 - tp: 25750.7363"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0421 - accuracy: 0.9441 - auc: 0.9879 - cross entropy: 0.1412 - fn: 2152.2500 - fp: 1091.0536 - loss: 0.1412 - prc: 0.9893 - precision: 0.9612 - recall: 0.9261 - tn: 27943.1777 - tp: 27181.5176"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0421 - accuracy: 0.9441 - auc: 0.9879 - cross entropy: 0.1411 - fn: 2264.1865 - fp: 1145.8306 - loss: 0.1411 - prc: 0.9893 - precision: 0.9612 - recall: 0.9262 - tn: 29417.7637 - tp: 28612.2207"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0421 - accuracy: 0.9442 - auc: 0.9879 - cross entropy: 0.1411 - fn: 2376.2903 - fp: 1200.6451 - loss: 0.1411 - prc: 0.9893 - precision: 0.9613 - recall: 0.9262 - tn: 30891.4512 - tp: 30043.6133"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0421 - accuracy: 0.9442 - auc: 0.9879 - cross entropy: 0.1411 - fn: 2488.2461 - fp: 1255.5692 - loss: 0.1411 - prc: 0.9893 - precision: 0.9613 - recall: 0.9263 - tn: 32367.2148 - tp: 31472.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0420 - accuracy: 0.9443 - auc: 0.9879 - cross entropy: 0.1410 - fn: 2599.6030 - fp: 1309.9706 - loss: 0.1410 - prc: 0.9893 - precision: 0.9614 - recall: 0.9263 - tn: 33845.6484 - tp: 32900.7812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0420 - accuracy: 0.9443 - auc: 0.9879 - cross entropy: 0.1410 - fn: 2711.3662 - fp: 1363.4507 - loss: 0.1410 - prc: 0.9893 - precision: 0.9614 - recall: 0.9263 - tn: 35324.4648 - tp: 34328.7188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0420 - accuracy: 0.9444 - auc: 0.9879 - cross entropy: 0.1409 - fn: 2822.8513 - fp: 1417.2433 - loss: 0.1409 - prc: 0.9893 - precision: 0.9615 - recall: 0.9264 - tn: 36804.3633 - tp: 35755.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 76/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0420 - accuracy: 0.9444 - auc: 0.9880 - cross entropy: 0.1409 - fn: 2897.0657 - fp: 1453.2236 - loss: 0.1409 - prc: 0.9893 - precision: 0.9615 - recall: 0.9264 - tn: 37791.4883 - tp: 36706.2227"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 79/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0420 - accuracy: 0.9444 - auc: 0.9880 - cross entropy: 0.1409 - fn: 3008.2278 - fp: 1507.7595 - loss: 0.1409 - prc: 0.9893 - precision: 0.9616 - recall: 0.9264 - tn: 39272.0898 - tp: 38131.9258"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 82/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0420 - accuracy: 0.9445 - auc: 0.9880 - cross entropy: 0.1409 - fn: 3118.9634 - fp: 1562.5366 - loss: 0.1409 - prc: 0.9893 - precision: 0.9616 - recall: 0.9265 - tn: 40753.5469 - tp: 39556.9531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 85/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9445 - auc: 0.9880 - cross entropy: 0.1408 - fn: 3230.0471 - fp: 1617.2118 - loss: 0.1408 - prc: 0.9893 - precision: 0.9616 - recall: 0.9265 - tn: 42234.1992 - tp: 40982.5430"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 88/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9445 - auc: 0.9880 - cross entropy: 0.1408 - fn: 3340.9092 - fp: 1671.6250 - loss: 0.1408 - prc: 0.9894 - precision: 0.9617 - recall: 0.9265 - tn: 43713.6250 - tp: 42409.8398"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 91/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9446 - auc: 0.9880 - cross entropy: 0.1408 - fn: 3451.4834 - fp: 1725.8792 - loss: 0.1408 - prc: 0.9894 - precision: 0.9617 - recall: 0.9266 - tn: 45193.0000 - tp: 43837.6367"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 94/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9446 - auc: 0.9880 - cross entropy: 0.1407 - fn: 3561.7874 - fp: 1780.4574 - loss: 0.1407 - prc: 0.9894 - precision: 0.9617 - recall: 0.9266 - tn: 46673.3945 - tp: 45264.3633"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 97/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9447 - auc: 0.9880 - cross entropy: 0.1407 - fn: 3672.2783 - fp: 1835.0206 - loss: 0.1407 - prc: 0.9894 - precision: 0.9618 - recall: 0.9266 - tn: 48153.0820 - tp: 46691.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m100/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9447 - auc: 0.9880 - cross entropy: 0.1407 - fn: 3783.2300 - fp: 1889.5500 - loss: 0.1407 - prc: 0.9894 - precision: 0.9618 - recall: 0.9267 - tn: 49630.8906 - tp: 48120.3281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m103/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0419 - accuracy: 0.9447 - auc: 0.9880 - cross entropy: 0.1406 - fn: 3894.2524 - fp: 1943.8350 - loss: 0.1406 - prc: 0.9894 - precision: 0.9618 - recall: 0.9267 - tn: 51109.5156 - tp: 49548.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m106/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9447 - auc: 0.9880 - cross entropy: 0.1406 - fn: 4005.2170 - fp: 1998.4623 - loss: 0.1406 - prc: 0.9894 - precision: 0.9618 - recall: 0.9267 - tn: 52588.9805 - tp: 50975.3398"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m109/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9448 - auc: 0.9880 - cross entropy: 0.1406 - fn: 4116.2842 - fp: 2052.9451 - loss: 0.1406 - prc: 0.9894 - precision: 0.9619 - recall: 0.9267 - tn: 54065.6680 - tp: 52405.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m112/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9448 - auc: 0.9880 - cross entropy: 0.1405 - fn: 4227.3394 - fp: 2107.2856 - loss: 0.1405 - prc: 0.9894 - precision: 0.9619 - recall: 0.9267 - tn: 55542.2227 - tp: 53835.1523"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m115/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9448 - auc: 0.9881 - cross entropy: 0.1405 - fn: 4338.3828 - fp: 2161.4434 - loss: 0.1405 - prc: 0.9894 - precision: 0.9619 - recall: 0.9268 - tn: 57019.3984 - tp: 55264.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m118/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9448 - auc: 0.9881 - cross entropy: 0.1405 - fn: 4449.2627 - fp: 2215.6187 - loss: 0.1405 - prc: 0.9894 - precision: 0.9619 - recall: 0.9268 - tn: 58496.6094 - tp: 56694.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m121/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9449 - auc: 0.9881 - cross entropy: 0.1404 - fn: 4560.3887 - fp: 2269.4297 - loss: 0.1404 - prc: 0.9894 - precision: 0.9620 - recall: 0.9268 - tn: 59974.6445 - tp: 58123.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m124/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9449 - auc: 0.9881 - cross entropy: 0.1404 - fn: 4671.6694 - fp: 2323.3708 - loss: 0.1404 - prc: 0.9894 - precision: 0.9620 - recall: 0.9268 - tn: 61452.8477 - tp: 59552.1133"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m127/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9449 - auc: 0.9881 - cross entropy: 0.1404 - fn: 4782.9526 - fp: 2377.1890 - loss: 0.1404 - prc: 0.9894 - precision: 0.9620 - recall: 0.9268 - tn: 62931.9297 - tp: 60979.9297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m130/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0418 - accuracy: 0.9449 - auc: 0.9881 - cross entropy: 0.1403 - fn: 4894.1846 - fp: 2430.8538 - loss: 0.1403 - prc: 0.9894 - precision: 0.9620 - recall: 0.9269 - tn: 64410.1758 - tp: 62408.7852"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m133/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9450 - auc: 0.9881 - cross entropy: 0.1403 - fn: 5005.2783 - fp: 2484.0676 - loss: 0.1403 - prc: 0.9894 - precision: 0.9621 - recall: 0.9269 - tn: 65888.8672 - tp: 63837.7891"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m136/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9450 - auc: 0.9881 - cross entropy: 0.1402 - fn: 5116.2646 - fp: 2537.1765 - loss: 0.1402 - prc: 0.9894 - precision: 0.9621 - recall: 0.9269 - tn: 67368.1094 - tp: 65266.4492"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m139/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9450 - auc: 0.9881 - cross entropy: 0.1402 - fn: 5226.9639 - fp: 2590.3167 - loss: 0.1402 - prc: 0.9894 - precision: 0.9621 - recall: 0.9269 - tn: 68848.1641 - tp: 66694.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m142/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9450 - auc: 0.9881 - cross entropy: 0.1402 - fn: 5337.9717 - fp: 2643.4929 - loss: 0.1402 - prc: 0.9894 - precision: 0.9622 - recall: 0.9269 - tn: 70327.5391 - tp: 68123.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m145/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9450 - auc: 0.9881 - cross entropy: 0.1401 - fn: 5449.3032 - fp: 2696.7173 - loss: 0.1401 - prc: 0.9894 - precision: 0.9622 - recall: 0.9269 - tn: 71805.4297 - tp: 69552.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m148/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9451 - auc: 0.9881 - cross entropy: 0.1401 - fn: 5560.4663 - fp: 2750.0676 - loss: 0.1401 - prc: 0.9894 - precision: 0.9622 - recall: 0.9269 - tn: 73283.9219 - tp: 70981.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m151/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0417 - accuracy: 0.9451 - auc: 0.9881 - cross entropy: 0.1400 - fn: 5671.4370 - fp: 2803.5630 - loss: 0.1400 - prc: 0.9895 - precision: 0.9622 - recall: 0.9270 - tn: 74763.3516 - tp: 72409.6484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m154/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9451 - auc: 0.9882 - cross entropy: 0.1400 - fn: 5782.1167 - fp: 2857.0845 - loss: 0.1400 - prc: 0.9895 - precision: 0.9622 - recall: 0.9270 - tn: 76242.7969 - tp: 73838.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m157/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9451 - auc: 0.9882 - cross entropy: 0.1400 - fn: 5892.5669 - fp: 2910.8218 - loss: 0.1400 - prc: 0.9895 - precision: 0.9623 - recall: 0.9270 - tn: 77722.5000 - tp: 75266.1094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m160/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9451 - auc: 0.9882 - cross entropy: 0.1399 - fn: 6002.9375 - fp: 2964.5249 - loss: 0.1399 - prc: 0.9895 - precision: 0.9623 - recall: 0.9270 - tn: 79202.3203 - tp: 76694.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m163/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9452 - auc: 0.9882 - cross entropy: 0.1399 - fn: 6113.3618 - fp: 3018.2024 - loss: 0.1399 - prc: 0.9895 - precision: 0.9623 - recall: 0.9270 - tn: 80682.0391 - tp: 78122.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m166/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9452 - auc: 0.9882 - cross entropy: 0.1398 - fn: 6223.8975 - fp: 3071.6748 - loss: 0.1398 - prc: 0.9895 - precision: 0.9623 - recall: 0.9270 - tn: 82161.4141 - tp: 79551.0156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m169/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9452 - auc: 0.9882 - cross entropy: 0.1398 - fn: 6334.7100 - fp: 3125.0295 - loss: 0.1398 - prc: 0.9895 - precision: 0.9623 - recall: 0.9270 - tn: 83640.6250 - tp: 80979.6406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m172/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0416 - accuracy: 0.9452 - auc: 0.9882 - cross entropy: 0.1398 - fn: 6445.1279 - fp: 3178.2559 - loss: 0.1398 - prc: 0.9895 - precision: 0.9624 - recall: 0.9271 - tn: 85121.0312 - tp: 82407.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m175/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9452 - auc: 0.9882 - cross entropy: 0.1397 - fn: 6555.3486 - fp: 3231.3486 - loss: 0.1397 - prc: 0.9895 - precision: 0.9624 - recall: 0.9271 - tn: 86602.0625 - tp: 83835.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m178/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9452 - auc: 0.9882 - cross entropy: 0.1397 - fn: 6665.7134 - fp: 3284.6348 - loss: 0.1397 - prc: 0.9895 - precision: 0.9624 - recall: 0.9271 - tn: 88082.7500 - tp: 85262.8984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m181/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9453 - auc: 0.9882 - cross entropy: 0.1397 - fn: 6775.9722 - fp: 3338.1050 - loss: 0.1397 - prc: 0.9895 - precision: 0.9624 - recall: 0.9271 - tn: 89563.6562 - tp: 86690.2656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m184/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9453 - auc: 0.9882 - cross entropy: 0.1396 - fn: 6886.0815 - fp: 3391.4131 - loss: 0.1396 - prc: 0.9895 - precision: 0.9624 - recall: 0.9271 - tn: 91044.6719 - tp: 88117.8281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m187/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9453 - auc: 0.9882 - cross entropy: 0.1396 - fn: 6995.9624 - fp: 3444.8235 - loss: 0.1396 - prc: 0.9895 - precision: 0.9624 - recall: 0.9271 - tn: 92526.1094 - tp: 89545.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m190/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9453 - auc: 0.9882 - cross entropy: 0.1395 - fn: 7105.7632 - fp: 3497.9790 - loss: 0.1395 - prc: 0.9895 - precision: 0.9625 - recall: 0.9271 - tn: 94008.3594 - tp: 90971.8984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m193/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9453 - auc: 0.9883 - cross entropy: 0.1395 - fn: 7215.4043 - fp: 3551.0881 - loss: 0.1395 - prc: 0.9895 - precision: 0.9625 - recall: 0.9272 - tn: 95490.7344 - tp: 92398.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m196/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0415 - accuracy: 0.9453 - auc: 0.9883 - cross entropy: 0.1395 - fn: 7324.7451 - fp: 3604.1990 - loss: 0.1395 - prc: 0.9895 - precision: 0.9625 - recall: 0.9272 - tn: 96973.6719 - tp: 93825.3906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m199/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9454 - auc: 0.9883 - cross entropy: 0.1394 - fn: 7434.0503 - fp: 3657.3215 - loss: 0.1394 - prc: 0.9895 - precision: 0.9625 - recall: 0.9272 - tn: 98456.5938 - tp: 95252.0391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m202/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9454 - auc: 0.9883 - cross entropy: 0.1394 - fn: 7543.3418 - fp: 3710.4158 - loss: 0.1394 - prc: 0.9895 - precision: 0.9625 - recall: 0.9272 - tn: 99940.4688 - tp: 96677.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m205/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9454 - auc: 0.9883 - cross entropy: 0.1393 - fn: 7652.5610 - fp: 3763.5903 - loss: 0.1393 - prc: 0.9896 - precision: 0.9625 - recall: 0.9272 - tn: 101423.5625 - tp: 98104.2812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m208/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9454 - auc: 0.9883 - cross entropy: 0.1393 - fn: 7761.6152 - fp: 3816.7644 - loss: 0.1393 - prc: 0.9896 - precision: 0.9626 - recall: 0.9272 - tn: 102906.4141 - tp: 99531.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m211/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9454 - auc: 0.9883 - cross entropy: 0.1392 - fn: 7870.6636 - fp: 3869.9385 - loss: 0.1392 - prc: 0.9896 - precision: 0.9626 - recall: 0.9273 - tn: 104389.0781 - tp: 100958.3203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m214/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9454 - auc: 0.9883 - cross entropy: 0.1392 - fn: 7979.7803 - fp: 3923.0420 - loss: 0.1392 - prc: 0.9896 - precision: 0.9626 - recall: 0.9273 - tn: 105871.4688 - tp: 102385.7109"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m217/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9455 - auc: 0.9883 - cross entropy: 0.1392 - fn: 8088.8066 - fp: 3975.9724 - loss: 0.1392 - prc: 0.9896 - precision: 0.9626 - recall: 0.9273 - tn: 107354.3672 - tp: 103812.8594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m220/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0414 - accuracy: 0.9455 - auc: 0.9883 - cross entropy: 0.1391 - fn: 8197.6543 - fp: 4028.8728 - loss: 0.1391 - prc: 0.9896 - precision: 0.9626 - recall: 0.9273 - tn: 108837.0000 - tp: 105240.4766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m223/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9455 - auc: 0.9883 - cross entropy: 0.1391 - fn: 8306.6768 - fp: 4081.6008 - loss: 0.1391 - prc: 0.9896 - precision: 0.9626 - recall: 0.9273 - tn: 110318.1484 - tp: 106669.5703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m226/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9455 - auc: 0.9883 - cross entropy: 0.1390 - fn: 8415.7305 - fp: 4134.2300 - loss: 0.1390 - prc: 0.9896 - precision: 0.9627 - recall: 0.9273 - tn: 111799.5703 - tp: 108098.4688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m229/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9455 - auc: 0.9884 - cross entropy: 0.1390 - fn: 8524.6855 - fp: 4187.0264 - loss: 0.1390 - prc: 0.9896 - precision: 0.9627 - recall: 0.9273 - tn: 113281.4219 - tp: 109526.8672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m232/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9455 - auc: 0.9884 - cross entropy: 0.1390 - fn: 8633.4609 - fp: 4239.7886 - loss: 0.1390 - prc: 0.9896 - precision: 0.9627 - recall: 0.9274 - tn: 114763.9688 - tp: 110954.7812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m235/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9455 - auc: 0.9884 - cross entropy: 0.1389 - fn: 8742.2725 - fp: 4292.5107 - loss: 0.1389 - prc: 0.9896 - precision: 0.9627 - recall: 0.9274 - tn: 116246.7031 - tp: 112382.5156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m238/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9456 - auc: 0.9884 - cross entropy: 0.1389 - fn: 8851.0928 - fp: 4345.2480 - loss: 0.1389 - prc: 0.9896 - precision: 0.9627 - recall: 0.9274 - tn: 117729.8516 - tp: 113809.8047"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m241/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9456 - auc: 0.9884 - cross entropy: 0.1388 - fn: 8959.7471 - fp: 4397.9668 - loss: 0.1388 - prc: 0.9896 - precision: 0.9627 - recall: 0.9274 - tn: 119213.0078 - tp: 115237.2812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m244/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0413 - accuracy: 0.9456 - auc: 0.9884 - cross entropy: 0.1388 - fn: 9068.2168 - fp: 4450.6187 - loss: 0.1388 - prc: 0.9896 - precision: 0.9627 - recall: 0.9274 - tn: 120695.9766 - tp: 116665.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m247/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9456 - auc: 0.9884 - cross entropy: 0.1388 - fn: 9176.5303 - fp: 4503.2104 - loss: 0.1388 - prc: 0.9896 - precision: 0.9627 - recall: 0.9274 - tn: 122179.2734 - tp: 118092.9844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m250/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9456 - auc: 0.9884 - cross entropy: 0.1387 - fn: 9284.8320 - fp: 4555.7642 - loss: 0.1387 - prc: 0.9896 - precision: 0.9628 - recall: 0.9274 - tn: 123662.5234 - tp: 119520.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m253/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9456 - auc: 0.9884 - cross entropy: 0.1387 - fn: 9393.0078 - fp: 4608.1621 - loss: 0.1387 - prc: 0.9896 - precision: 0.9628 - recall: 0.9275 - tn: 125145.8672 - tp: 120948.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m256/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9457 - auc: 0.9884 - cross entropy: 0.1386 - fn: 9501.0469 - fp: 4660.5195 - loss: 0.1386 - prc: 0.9896 - precision: 0.9628 - recall: 0.9275 - tn: 126629.5469 - tp: 122376.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m259/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9457 - auc: 0.9884 - cross entropy: 0.1386 - fn: 9609.0078 - fp: 4712.6797 - loss: 0.1386 - prc: 0.9897 - precision: 0.9628 - recall: 0.9275 - tn: 128113.9297 - tp: 123804.3828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m262/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9457 - auc: 0.9884 - cross entropy: 0.1386 - fn: 9716.8477 - fp: 4764.6641 - loss: 0.1386 - prc: 0.9897 - precision: 0.9628 - recall: 0.9275 - tn: 129598.1172 - tp: 125232.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m265/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9457 - auc: 0.9884 - cross entropy: 0.1385 - fn: 9824.6562 - fp: 4816.6831 - loss: 0.1385 - prc: 0.9897 - precision: 0.9628 - recall: 0.9275 - tn: 131082.1719 - tp: 126660.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m268/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0412 - accuracy: 0.9457 - auc: 0.9885 - cross entropy: 0.1385 - fn: 9932.3359 - fp: 4868.6641 - loss: 0.1385 - prc: 0.9897 - precision: 0.9628 - recall: 0.9275 - tn: 132565.7031 - tp: 128089.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m271/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0411 - accuracy: 0.9457 - auc: 0.9885 - cross entropy: 0.1384 - fn: 10039.7715 - fp: 4920.4282 - loss: 0.1384 - prc: 0.9897 - precision: 0.9629 - recall: 0.9276 - tn: 134049.2344 - tp: 129518.5703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m274/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0411 - accuracy: 0.9458 - auc: 0.9885 - cross entropy: 0.1384 - fn: 10147.1748 - fp: 4971.9746 - loss: 0.1384 - prc: 0.9897 - precision: 0.9629 - recall: 0.9276 - tn: 135532.4844 - tp: 130948.3672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m277/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0411 - accuracy: 0.9458 - auc: 0.9885 - cross entropy: 0.1383 - fn: 10254.4336 - fp: 5023.3608 - loss: 0.1383 - prc: 0.9897 - precision: 0.9629 - recall: 0.9276 - tn: 137015.0938 - tp: 132379.1094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0411 - accuracy: 0.9458 - auc: 0.9885 - cross entropy: 0.1383 - fn: 10325.6631 - fp: 5057.5518 - loss: 0.1383 - prc: 0.9897 - precision: 0.9629 - recall: 0.9276 - tn: 137999.7344 - tp: 133329.7031 - val_Brier score: 0.0166 - val_accuracy: 0.9824 - val_auc: 0.9891 - val_cross entropy: 0.0745 - val_fn: 4.0000 - val_fp: 798.0000 - val_loss: 0.0745 - val_prc: 0.7324 - val_precision: 0.0890 - val_recall: 0.9512 - val_tn: 44689.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 5/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - Brier score: 0.0376 - accuracy: 0.9492 - auc: 0.9908 - cross entropy: 0.1224 - fn: 70.0000 - fp: 34.0000 - loss: 0.1224 - prc: 0.9917 - precision: 0.9657 - recall: 0.9318 - tn: 988.0000 - tp: 956.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 15ms/step - Brier score: 0.0367 - accuracy: 0.9510 - auc: 0.9912 - cross entropy: 0.1245 - fn: 204.8000 - fp: 94.4000 - loss: 0.1245 - prc: 0.9917 - precision: 0.9676 - recall: 0.9325 - tn: 3001.2000 - tp: 2843.6001"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9911 - cross entropy: 0.1252 - fn: 307.7500 - fp: 145.8750 - loss: 0.1252 - prc: 0.9916 - precision: 0.9672 - recall: 0.9328 - tn: 4466.8750 - tp: 4295.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0368 - accuracy: 0.9508 - auc: 0.9911 - cross entropy: 0.1249 - fn: 410.3636 - fp: 192.4545 - loss: 0.1249 - prc: 0.9916 - precision: 0.9674 - recall: 0.9330 - tn: 5943.2729 - tp: 5741.9092"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1248 - fn: 512.5714 - fp: 239.6429 - loss: 0.1248 - prc: 0.9916 - precision: 0.9675 - recall: 0.9331 - tn: 7431.2856 - tp: 7176.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0369 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1249 - fn: 616.1765 - fp: 287.2941 - loss: 0.1249 - prc: 0.9916 - precision: 0.9676 - recall: 0.9330 - tn: 8924.1768 - tp: 8604.3525"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0369 - accuracy: 0.9509 - auc: 0.9910 - cross entropy: 0.1249 - fn: 719.7500 - fp: 335.9500 - loss: 0.1249 - prc: 0.9916 - precision: 0.9675 - recall: 0.9330 - tn: 10415.2002 - tp: 10033.0996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0369 - accuracy: 0.9509 - auc: 0.9910 - cross entropy: 0.1248 - fn: 823.5652 - fp: 384.0000 - loss: 0.1248 - prc: 0.9916 - precision: 0.9675 - recall: 0.9330 - tn: 11900.3916 - tp: 11468.0439"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1248 - fn: 926.3077 - fp: 433.1923 - loss: 0.1248 - prc: 0.9916 - precision: 0.9675 - recall: 0.9330 - tn: 13386.2305 - tp: 12902.2695"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1028.5862 - fp: 483.5517 - loss: 0.1248 - prc: 0.9916 - precision: 0.9674 - recall: 0.9330 - tn: 14871.5859 - tp: 14336.2754"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1249 - fn: 1132.7500 - fp: 533.2188 - loss: 0.1249 - prc: 0.9916 - precision: 0.9674 - recall: 0.9330 - tn: 16355.2812 - tp: 15770.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1235.7428 - fp: 582.1143 - loss: 0.1248 - prc: 0.9916 - precision: 0.9674 - recall: 0.9330 - tn: 17836.4570 - tp: 17209.6855"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1339.8158 - fp: 631.0000 - loss: 0.1248 - prc: 0.9916 - precision: 0.9674 - recall: 0.9330 - tn: 19315.9473 - tp: 18649.2363"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1444.6097 - fp: 681.0488 - loss: 0.1248 - prc: 0.9916 - precision: 0.9673 - recall: 0.9329 - tn: 20797.0977 - tp: 20085.2441"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1549.2954 - fp: 731.7045 - loss: 0.1248 - prc: 0.9916 - precision: 0.9673 - recall: 0.9329 - tn: 22276.7500 - tp: 21522.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1653.7234 - fp: 782.9575 - loss: 0.1248 - prc: 0.9916 - precision: 0.9672 - recall: 0.9329 - tn: 23754.5957 - tp: 22960.7227"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1758.2000 - fp: 833.4800 - loss: 0.1248 - prc: 0.9916 - precision: 0.9672 - recall: 0.9329 - tn: 25230.0801 - tp: 24402.2402"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1248 - fn: 1862.5471 - fp: 883.7358 - loss: 0.1248 - prc: 0.9916 - precision: 0.9671 - recall: 0.9329 - tn: 26709.0195 - tp: 25840.6973"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9505 - auc: 0.9909 - cross entropy: 0.1248 - fn: 1967.1428 - fp: 934.2500 - loss: 0.1248 - prc: 0.9916 - precision: 0.9671 - recall: 0.9328 - tn: 28190.8027 - tp: 27275.8027"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9505 - auc: 0.9909 - cross entropy: 0.1248 - fn: 2071.7627 - fp: 984.8305 - loss: 0.1248 - prc: 0.9916 - precision: 0.9671 - recall: 0.9328 - tn: 29672.6602 - tp: 28710.7461"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1248 - fn: 2175.7419 - fp: 1035.1613 - loss: 0.1248 - prc: 0.9916 - precision: 0.9670 - recall: 0.9328 - tn: 31153.5000 - tp: 30147.5977"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1248 - fn: 2279.7231 - fp: 1085.3077 - loss: 0.1248 - prc: 0.9916 - precision: 0.9670 - recall: 0.9328 - tn: 32632.2930 - tp: 31586.6777"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1248 - fn: 2383.2354 - fp: 1135.0883 - loss: 0.1248 - prc: 0.9916 - precision: 0.9670 - recall: 0.9328 - tn: 34111.9844 - tp: 33025.6914"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1248 - fn: 2486.3098 - fp: 1184.4507 - loss: 0.1248 - prc: 0.9916 - precision: 0.9670 - recall: 0.9328 - tn: 35594.3516 - tp: 34462.8867"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 2588.8918 - fp: 1233.8243 - loss: 0.1247 - prc: 0.9916 - precision: 0.9670 - recall: 0.9328 - tn: 37076.6758 - tp: 35900.6094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 77/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 2691.1558 - fp: 1284.0520 - loss: 0.1247 - prc: 0.9916 - precision: 0.9670 - recall: 0.9328 - tn: 38558.2070 - tp: 37338.5859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 80/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 2793.7749 - fp: 1334.0875 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9328 - tn: 40038.9375 - tp: 38777.1992"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 83/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 2896.2410 - fp: 1383.9518 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9328 - tn: 41519.4102 - tp: 40216.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 86/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 2998.5349 - fp: 1433.9767 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9329 - tn: 42999.8125 - tp: 41655.6758"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 89/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 3100.4158 - fp: 1484.3707 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9329 - tn: 44480.9219 - tp: 43094.2930"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 92/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 3202.0869 - fp: 1534.4783 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9329 - tn: 45962.1211 - tp: 44533.3164"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 95/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 3303.7473 - fp: 1584.4736 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9329 - tn: 47442.6641 - tp: 45973.1172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 98/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1247 - fn: 3405.1326 - fp: 1634.3877 - loss: 0.1247 - prc: 0.9916 - precision: 0.9669 - recall: 0.9329 - tn: 48922.5625 - tp: 47413.9180"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m101/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1246 - fn: 3506.5049 - fp: 1684.2772 - loss: 0.1246 - prc: 0.9916 - precision: 0.9669 - recall: 0.9330 - tn: 50403.3555 - tp: 48853.8633"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m104/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1246 - fn: 3607.8845 - fp: 1733.8462 - loss: 0.1246 - prc: 0.9916 - precision: 0.9669 - recall: 0.9330 - tn: 51885.6055 - tp: 50292.6641"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m107/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1246 - fn: 3708.8599 - fp: 1783.5701 - loss: 0.1246 - prc: 0.9916 - precision: 0.9669 - recall: 0.9330 - tn: 53367.1211 - tp: 51732.4492"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m110/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1246 - fn: 3809.9182 - fp: 1832.9546 - loss: 0.1246 - prc: 0.9916 - precision: 0.9669 - recall: 0.9330 - tn: 54847.1836 - tp: 53173.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m113/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0371 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1246 - fn: 3911.0884 - fp: 1882.5841 - loss: 0.1246 - prc: 0.9916 - precision: 0.9668 - recall: 0.9330 - tn: 56327.5586 - tp: 54614.7695"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m116/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1245 - fn: 4012.3362 - fp: 1932.1897 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9331 - tn: 57809.2148 - tp: 56054.2578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m119/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1245 - fn: 4113.4873 - fp: 1981.5210 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9331 - tn: 59291.5703 - tp: 57493.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m122/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9504 - auc: 0.9909 - cross entropy: 0.1245 - fn: 4214.4673 - fp: 2030.8115 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9331 - tn: 60774.4609 - tp: 58932.2617"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m125/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9909 - cross entropy: 0.1245 - fn: 4315.2881 - fp: 2080.0000 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9331 - tn: 62257.3359 - tp: 60371.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m128/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9909 - cross entropy: 0.1245 - fn: 4416.1719 - fp: 2128.9375 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9331 - tn: 63739.4375 - tp: 61811.4531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m131/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9909 - cross entropy: 0.1245 - fn: 4516.9922 - fp: 2177.8550 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9331 - tn: 65222.1211 - tp: 63251.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m134/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1245 - fn: 4617.7759 - fp: 2226.6418 - loss: 0.1245 - prc: 0.9916 - precision: 0.9668 - recall: 0.9332 - tn: 66704.6094 - tp: 64690.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m137/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1245 - fn: 4718.4746 - fp: 2275.3213 - loss: 0.1245 - prc: 0.9916 - precision: 0.9669 - recall: 0.9332 - tn: 68186.6406 - tp: 66131.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m140/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1244 - fn: 4818.9785 - fp: 2324.2144 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9332 - tn: 69669.7578 - tp: 67571.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m143/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1244 - fn: 4919.4824 - fp: 2373.0979 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9332 - tn: 71154.2500 - tp: 69009.1641"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m146/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1244 - fn: 5020.0547 - fp: 2422.2056 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9332 - tn: 72638.4688 - tp: 70447.2734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m149/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1244 - fn: 5120.2686 - fp: 2471.2617 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9333 - tn: 74123.2188 - tp: 71885.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m152/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1244 - fn: 5220.5195 - fp: 2520.2434 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9333 - tn: 75607.8438 - tp: 73323.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m155/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9505 - auc: 0.9910 - cross entropy: 0.1244 - fn: 5320.7935 - fp: 2569.1807 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9333 - tn: 77091.9062 - tp: 74762.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m158/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1244 - fn: 5421.1201 - fp: 2618.0823 - loss: 0.1244 - prc: 0.9916 - precision: 0.9669 - recall: 0.9333 - tn: 78575.9062 - tp: 76200.8906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m161/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 5521.3354 - fp: 2667.1863 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9333 - tn: 80059.3906 - tp: 77640.0859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m164/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 5621.5913 - fp: 2716.4146 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9333 - tn: 81542.8750 - tp: 79079.1172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m167/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 5721.7427 - fp: 2765.7605 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9334 - tn: 83026.5234 - tp: 80517.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m170/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 5821.6177 - fp: 2815.1118 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9334 - tn: 84510.4062 - tp: 81956.8672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m173/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 5921.1216 - fp: 2864.3816 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9334 - tn: 85994.7656 - tp: 83395.7344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m176/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 6020.3296 - fp: 2913.7500 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9334 - tn: 87479.3203 - tp: 84834.6016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m179/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 6119.5474 - fp: 2962.9329 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9334 - tn: 88964.4375 - tp: 86273.0781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m182/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1243 - fn: 6218.6758 - fp: 3012.0769 - loss: 0.1243 - prc: 0.9916 - precision: 0.9669 - recall: 0.9335 - tn: 90450.0078 - tp: 87711.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m185/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6317.7568 - fp: 3061.2107 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9335 - tn: 91935.7344 - tp: 89149.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m188/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0370 - accuracy: 0.9506 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6416.7607 - fp: 3110.2554 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9335 - tn: 93420.9141 - tp: 90588.0703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m191/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6515.7593 - fp: 3159.3613 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9335 - tn: 94905.7422 - tp: 92027.1328"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m194/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6614.8506 - fp: 3208.4587 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9335 - tn: 96389.7188 - tp: 93466.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m197/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6713.9746 - fp: 3257.4468 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9336 - tn: 97873.2812 - tp: 94907.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m200/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6812.9551 - fp: 3306.5049 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9336 - tn: 99357.6328 - tp: 96346.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m203/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1242 - fn: 6911.9014 - fp: 3355.6355 - loss: 0.1242 - prc: 0.9916 - precision: 0.9669 - recall: 0.9336 - tn: 100841.9688 - tp: 97786.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m206/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1241 - fn: 7010.6553 - fp: 3404.6409 - loss: 0.1241 - prc: 0.9916 - precision: 0.9669 - recall: 0.9336 - tn: 102326.6719 - tp: 99226.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m209/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1241 - fn: 7109.2393 - fp: 3453.5215 - loss: 0.1241 - prc: 0.9916 - precision: 0.9669 - recall: 0.9336 - tn: 103811.1953 - tp: 100666.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m212/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1241 - fn: 7207.7783 - fp: 3502.4905 - loss: 0.1241 - prc: 0.9916 - precision: 0.9669 - recall: 0.9337 - tn: 105296.0625 - tp: 102105.6719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m215/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1241 - fn: 7306.2324 - fp: 3551.3860 - loss: 0.1241 - prc: 0.9916 - precision: 0.9669 - recall: 0.9337 - tn: 106781.3047 - tp: 103545.0781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m218/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9507 - auc: 0.9910 - cross entropy: 0.1241 - fn: 7404.6240 - fp: 3600.1514 - loss: 0.1241 - prc: 0.9916 - precision: 0.9669 - recall: 0.9337 - tn: 108267.1328 - tp: 104984.0938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m221/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1241 - fn: 7502.8369 - fp: 3648.7917 - loss: 0.1241 - prc: 0.9917 - precision: 0.9669 - recall: 0.9337 - tn: 109752.8359 - tp: 106423.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m224/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1240 - fn: 7600.9243 - fp: 3697.3572 - loss: 0.1240 - prc: 0.9917 - precision: 0.9669 - recall: 0.9337 - tn: 111238.3984 - tp: 107863.3203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m227/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1240 - fn: 7698.7578 - fp: 3745.9692 - loss: 0.1240 - prc: 0.9917 - precision: 0.9669 - recall: 0.9337 - tn: 112724.0547 - tp: 109303.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m230/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1240 - fn: 7796.6606 - fp: 3794.5784 - loss: 0.1240 - prc: 0.9917 - precision: 0.9669 - recall: 0.9338 - tn: 114209.9922 - tp: 110742.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m233/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1240 - fn: 7894.5879 - fp: 3843.0386 - loss: 0.1240 - prc: 0.9917 - precision: 0.9669 - recall: 0.9338 - tn: 115696.1562 - tp: 112182.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m236/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0369 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1239 - fn: 7992.3350 - fp: 3891.3093 - loss: 0.1239 - prc: 0.9917 - precision: 0.9669 - recall: 0.9338 - tn: 117183.3438 - tp: 113621.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m239/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1239 - fn: 8089.9287 - fp: 3939.4478 - loss: 0.1239 - prc: 0.9917 - precision: 0.9669 - recall: 0.9338 - tn: 118670.8906 - tp: 115059.7344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m242/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9508 - auc: 0.9910 - cross entropy: 0.1239 - fn: 8187.4751 - fp: 3987.5042 - loss: 0.1239 - prc: 0.9917 - precision: 0.9669 - recall: 0.9338 - tn: 120157.3516 - tp: 116499.6641"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m245/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1239 - fn: 8284.9873 - fp: 4035.4775 - loss: 0.1239 - prc: 0.9917 - precision: 0.9669 - recall: 0.9339 - tn: 121643.7344 - tp: 117939.7969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m248/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1239 - fn: 8382.4473 - fp: 4083.5847 - loss: 0.1239 - prc: 0.9917 - precision: 0.9669 - recall: 0.9339 - tn: 123130.3281 - tp: 119379.6406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m251/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1238 - fn: 8479.7969 - fp: 4131.7290 - loss: 0.1238 - prc: 0.9917 - precision: 0.9669 - recall: 0.9339 - tn: 124617.5625 - tp: 120818.9141"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m254/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1238 - fn: 8577.1299 - fp: 4179.6455 - loss: 0.1238 - prc: 0.9917 - precision: 0.9669 - recall: 0.9339 - tn: 126105.3828 - tp: 122257.8438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m257/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1238 - fn: 8674.5332 - fp: 4227.4395 - loss: 0.1238 - prc: 0.9917 - precision: 0.9669 - recall: 0.9339 - tn: 127592.4531 - tp: 123697.5703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m260/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1238 - fn: 8772.0195 - fp: 4275.2847 - loss: 0.1238 - prc: 0.9917 - precision: 0.9669 - recall: 0.9340 - tn: 129078.9844 - tp: 125137.7188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m263/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1237 - fn: 8869.4795 - fp: 4323.1445 - loss: 0.1237 - prc: 0.9917 - precision: 0.9669 - recall: 0.9340 - tn: 130565.3438 - tp: 126578.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m266/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1237 - fn: 8966.8643 - fp: 4370.9961 - loss: 0.1237 - prc: 0.9917 - precision: 0.9669 - recall: 0.9340 - tn: 132051.6094 - tp: 128018.5312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m269/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9509 - auc: 0.9911 - cross entropy: 0.1237 - fn: 9064.3945 - fp: 4418.7808 - loss: 0.1237 - prc: 0.9917 - precision: 0.9669 - recall: 0.9340 - tn: 133537.7188 - tp: 129459.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m272/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9510 - auc: 0.9911 - cross entropy: 0.1237 - fn: 9161.8828 - fp: 4466.5220 - loss: 0.1237 - prc: 0.9917 - precision: 0.9670 - recall: 0.9340 - tn: 135023.8750 - tp: 130899.7266"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m275/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9510 - auc: 0.9911 - cross entropy: 0.1236 - fn: 9259.3818 - fp: 4514.1855 - loss: 0.1236 - prc: 0.9917 - precision: 0.9670 - recall: 0.9341 - tn: 136510.7344 - tp: 132339.7031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0368 - accuracy: 0.9510 - auc: 0.9911 - cross entropy: 0.1236 - fn: 9356.7051 - fp: 4561.8203 - loss: 0.1236 - prc: 0.9917 - precision: 0.9670 - recall: 0.9341 - tn: 137997.5000 - tp: 133779.9844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 20ms/step - Brier score: 0.0367 - accuracy: 0.9510 - auc: 0.9911 - cross entropy: 0.1236 - fn: 9388.8965 - fp: 4577.5771 - loss: 0.1236 - prc: 0.9917 - precision: 0.9670 - recall: 0.9341 - tn: 138489.5000 - tp: 134256.6875 - val_Brier score: 0.0148 - val_accuracy: 0.9843 - val_auc: 0.9893 - val_cross entropy: 0.0651 - val_fn: 4.0000 - val_fp: 713.0000 - val_loss: 0.0651 - val_prc: 0.7189 - val_precision: 0.0986 - val_recall: 0.9512 - val_tn: 44774.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - Brier score: 0.0353 - accuracy: 0.9526 - auc: 0.9919 - cross entropy: 0.1172 - fn: 63.0000 - fp: 34.0000 - loss: 0.1172 - prc: 0.9922 - precision: 0.9649 - recall: 0.9368 - tn: 1017.0000 - tp: 934.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0342 - accuracy: 0.9547 - auc: 0.9926 - cross entropy: 0.1137 - fn: 155.0000 - fp: 74.7500 - loss: 0.1137 - prc: 0.9929 - precision: 0.9687 - recall: 0.9384 - tn: 2516.5000 - tp: 2373.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 19ms/step - Brier score: 0.0340 - accuracy: 0.9549 - auc: 0.9928 - cross entropy: 0.1129 - fn: 248.7143 - fp: 118.7143 - loss: 0.1129 - prc: 0.9929 - precision: 0.9692 - recall: 0.9385 - tn: 4024.4285 - tp: 3800.1428"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 10/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 19ms/step - Brier score: 0.0340 - accuracy: 0.9549 - auc: 0.9927 - cross entropy: 0.1130 - fn: 344.6000 - fp: 161.9000 - loss: 0.1130 - prc: 0.9929 - precision: 0.9695 - recall: 0.9383 - tn: 5524.7998 - tp: 5232.7002"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 13/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 19ms/step - Brier score: 0.0341 - accuracy: 0.9548 - auc: 0.9927 - cross entropy: 0.1136 - fn: 441.9231 - fp: 207.5385 - loss: 0.1136 - prc: 0.9929 - precision: 0.9695 - recall: 0.9381 - tn: 7010.7690 - tp: 6675.7690"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 16/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0342 - accuracy: 0.9546 - auc: 0.9926 - cross entropy: 0.1139 - fn: 539.3750 - fp: 253.0625 - loss: 0.1139 - prc: 0.9928 - precision: 0.9696 - recall: 0.9380 - tn: 8493.1250 - tp: 8122.4375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 19/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0342 - accuracy: 0.9546 - auc: 0.9926 - cross entropy: 0.1140 - fn: 634.0526 - fp: 298.9474 - loss: 0.1140 - prc: 0.9928 - precision: 0.9695 - recall: 0.9380 - tn: 9981.0527 - tp: 9565.9473"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 22/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0342 - accuracy: 0.9545 - auc: 0.9926 - cross entropy: 0.1141 - fn: 726.2273 - fp: 347.0909 - loss: 0.1141 - prc: 0.9928 - precision: 0.9694 - recall: 0.9381 - tn: 11466.1367 - tp: 11012.5459"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 25/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0342 - accuracy: 0.9545 - auc: 0.9926 - cross entropy: 0.1142 - fn: 818.3200 - fp: 395.0400 - loss: 0.1142 - prc: 0.9928 - precision: 0.9693 - recall: 0.9383 - tn: 12951.1602 - tp: 12459.4805"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 28/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0342 - accuracy: 0.9546 - auc: 0.9926 - cross entropy: 0.1142 - fn: 909.8214 - fp: 441.7500 - loss: 0.1142 - prc: 0.9928 - precision: 0.9693 - recall: 0.9384 - tn: 14431.1074 - tp: 13913.3213"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 31/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0342 - accuracy: 0.9546 - auc: 0.9926 - cross entropy: 0.1142 - fn: 1001.3871 - fp: 487.4516 - loss: 0.1142 - prc: 0.9928 - precision: 0.9693 - recall: 0.9385 - tn: 15913.2900 - tp: 15365.8711"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 34/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0342 - accuracy: 0.9546 - auc: 0.9926 - cross entropy: 0.1142 - fn: 1093.2354 - fp: 531.9706 - loss: 0.1142 - prc: 0.9928 - precision: 0.9694 - recall: 0.9386 - tn: 17396.3535 - tp: 16818.4414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 37/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0342 - accuracy: 0.9547 - auc: 0.9926 - cross entropy: 0.1141 - fn: 1185.0000 - fp: 576.0270 - loss: 0.1141 - prc: 0.9928 - precision: 0.9694 - recall: 0.9387 - tn: 18871.8105 - tp: 18279.1621"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 39/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0342 - accuracy: 0.9547 - auc: 0.9926 - cross entropy: 0.1141 - fn: 1246.4103 - fp: 605.2308 - loss: 0.1141 - prc: 0.9928 - precision: 0.9694 - recall: 0.9388 - tn: 19855.7695 - tp: 19252.5898"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 42/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0341 - accuracy: 0.9547 - auc: 0.9926 - cross entropy: 0.1141 - fn: 1338.4524 - fp: 649.8571 - loss: 0.1141 - prc: 0.9929 - precision: 0.9695 - recall: 0.9389 - tn: 21334.0234 - tp: 20709.6660"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 45/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0341 - accuracy: 0.9548 - auc: 0.9926 - cross entropy: 0.1140 - fn: 1430.3778 - fp: 694.6445 - loss: 0.1140 - prc: 0.9929 - precision: 0.9695 - recall: 0.9389 - tn: 22816.5781 - tp: 22162.4004"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 48/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0341 - accuracy: 0.9548 - auc: 0.9926 - cross entropy: 0.1140 - fn: 1521.8334 - fp: 739.6042 - loss: 0.1140 - prc: 0.9929 - precision: 0.9695 - recall: 0.9390 - tn: 24299.4160 - tp: 23615.1465"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 51/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0341 - accuracy: 0.9548 - auc: 0.9926 - cross entropy: 0.1139 - fn: 1613.0000 - fp: 784.1961 - loss: 0.1139 - prc: 0.9929 - precision: 0.9695 - recall: 0.9391 - tn: 25784.8828 - tp: 25065.9219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 54/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0341 - accuracy: 0.9549 - auc: 0.9926 - cross entropy: 0.1139 - fn: 1704.2963 - fp: 828.4445 - loss: 0.1139 - prc: 0.9929 - precision: 0.9696 - recall: 0.9391 - tn: 27271.0371 - tp: 26516.2227"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 57/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0340 - accuracy: 0.9549 - auc: 0.9926 - cross entropy: 0.1138 - fn: 1794.8422 - fp: 872.5439 - loss: 0.1138 - prc: 0.9929 - precision: 0.9696 - recall: 0.9392 - tn: 28758.1230 - tp: 27966.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 60/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0340 - accuracy: 0.9550 - auc: 0.9926 - cross entropy: 0.1138 - fn: 1884.3500 - fp: 916.2500 - loss: 0.1138 - prc: 0.9929 - precision: 0.9696 - recall: 0.9393 - tn: 30248.1992 - tp: 29415.1992"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 63/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0340 - accuracy: 0.9550 - auc: 0.9926 - cross entropy: 0.1137 - fn: 1974.0952 - fp: 959.8571 - loss: 0.1137 - prc: 0.9929 - precision: 0.9697 - recall: 0.9394 - tn: 31739.0312 - tp: 30863.0156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 66/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0340 - accuracy: 0.9550 - auc: 0.9926 - cross entropy: 0.1137 - fn: 2063.9697 - fp: 1003.8030 - loss: 0.1137 - prc: 0.9929 - precision: 0.9697 - recall: 0.9394 - tn: 33230.0156 - tp: 32310.2129"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 69/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0339 - accuracy: 0.9551 - auc: 0.9927 - cross entropy: 0.1136 - fn: 2153.6956 - fp: 1047.9420 - loss: 0.1136 - prc: 0.9929 - precision: 0.9697 - recall: 0.9395 - tn: 34720.8242 - tp: 33757.5352"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 72/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0339 - accuracy: 0.9551 - auc: 0.9927 - cross entropy: 0.1136 - fn: 2243.6667 - fp: 1091.9166 - loss: 0.1136 - prc: 0.9929 - precision: 0.9697 - recall: 0.9395 - tn: 36213.1680 - tp: 35203.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 75/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0339 - accuracy: 0.9551 - auc: 0.9927 - cross entropy: 0.1135 - fn: 2333.6799 - fp: 1136.5333 - loss: 0.1135 - prc: 0.9929 - precision: 0.9697 - recall: 0.9396 - tn: 37705.9453 - tp: 36647.8398"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 78/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0339 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1135 - fn: 2423.9487 - fp: 1181.4615 - loss: 0.1135 - prc: 0.9930 - precision: 0.9697 - recall: 0.9396 - tn: 39197.9219 - tp: 38092.6680"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 81/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0339 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1135 - fn: 2514.3704 - fp: 1226.8395 - loss: 0.1135 - prc: 0.9930 - precision: 0.9697 - recall: 0.9397 - tn: 40688.7891 - tp: 39538.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 84/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0339 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1135 - fn: 2604.8333 - fp: 1272.6666 - loss: 0.1135 - prc: 0.9930 - precision: 0.9697 - recall: 0.9397 - tn: 42179.7383 - tp: 40982.7617"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 87/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1134 - fn: 2695.2759 - fp: 1318.5172 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9397 - tn: 43670.2188 - tp: 42427.9883"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 90/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1134 - fn: 2785.3889 - fp: 1364.4333 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9398 - tn: 45159.4570 - tp: 43874.7227"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 93/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1134 - fn: 2875.3225 - fp: 1410.5591 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9398 - tn: 46649.8828 - tp: 45320.2383"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 96/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1134 - fn: 2965.1250 - fp: 1457.0416 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9398 - tn: 48141.8633 - tp: 46763.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 99/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9552 - auc: 0.9927 - cross entropy: 0.1134 - fn: 3054.6667 - fp: 1503.7778 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9399 - tn: 49635.7891 - tp: 48205.7695"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m102/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1134 - fn: 3144.0981 - fp: 1550.3040 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9399 - tn: 51128.3438 - tp: 49649.2539"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m105/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1134 - fn: 3233.7144 - fp: 1596.4476 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9399 - tn: 52621.4766 - tp: 51092.3633"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m108/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1134 - fn: 3323.2314 - fp: 1642.1296 - loss: 0.1134 - prc: 0.9930 - precision: 0.9697 - recall: 0.9400 - tn: 54116.3047 - tp: 52534.3320"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m111/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1133 - fn: 3412.5676 - fp: 1687.8558 - loss: 0.1133 - prc: 0.9930 - precision: 0.9697 - recall: 0.9400 - tn: 55610.4688 - tp: 53977.1094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m114/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1133 - fn: 3501.9473 - fp: 1733.8596 - loss: 0.1133 - prc: 0.9930 - precision: 0.9697 - recall: 0.9400 - tn: 57103.0000 - tp: 55421.1914"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m117/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1133 - fn: 3591.3760 - fp: 1779.6154 - loss: 0.1133 - prc: 0.9930 - precision: 0.9696 - recall: 0.9401 - tn: 58594.1523 - tp: 56866.8555"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m120/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0338 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1133 - fn: 3680.4751 - fp: 1824.9667 - loss: 0.1133 - prc: 0.9930 - precision: 0.9696 - recall: 0.9401 - tn: 60086.4180 - tp: 58312.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m123/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9553 - auc: 0.9927 - cross entropy: 0.1133 - fn: 3769.6016 - fp: 1870.3090 - loss: 0.1133 - prc: 0.9930 - precision: 0.9696 - recall: 0.9401 - tn: 61579.6406 - tp: 59756.4453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m126/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1133 - fn: 3858.6428 - fp: 1915.6666 - loss: 0.1133 - prc: 0.9930 - precision: 0.9696 - recall: 0.9401 - tn: 63073.0625 - tp: 61200.6289"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m129/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1132 - fn: 3947.7673 - fp: 1961.0698 - loss: 0.1132 - prc: 0.9930 - precision: 0.9696 - recall: 0.9402 - tn: 64567.2773 - tp: 62643.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m132/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1132 - fn: 4036.4622 - fp: 2006.3409 - loss: 0.1132 - prc: 0.9930 - precision: 0.9696 - recall: 0.9402 - tn: 66061.3438 - tp: 64087.8555"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m135/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1132 - fn: 4124.9556 - fp: 2051.6223 - loss: 0.1132 - prc: 0.9930 - precision: 0.9696 - recall: 0.9402 - tn: 67556.5391 - tp: 65530.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m138/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1132 - fn: 4213.7969 - fp: 2096.9783 - loss: 0.1132 - prc: 0.9930 - precision: 0.9696 - recall: 0.9403 - tn: 69051.0469 - tp: 66974.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m141/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1132 - fn: 4302.3901 - fp: 2142.2695 - loss: 0.1132 - prc: 0.9930 - precision: 0.9696 - recall: 0.9403 - tn: 70544.6250 - tp: 68418.7188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m144/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9554 - auc: 0.9927 - cross entropy: 0.1132 - fn: 4390.7568 - fp: 2187.5486 - loss: 0.1132 - prc: 0.9930 - precision: 0.9696 - recall: 0.9403 - tn: 72038.0859 - tp: 69863.6094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m147/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9555 - auc: 0.9927 - cross entropy: 0.1131 - fn: 4479.1836 - fp: 2232.8503 - loss: 0.1131 - prc: 0.9930 - precision: 0.9696 - recall: 0.9403 - tn: 73531.2031 - tp: 71308.7656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m150/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9555 - auc: 0.9927 - cross entropy: 0.1131 - fn: 4567.5068 - fp: 2278.1133 - loss: 0.1131 - prc: 0.9930 - precision: 0.9696 - recall: 0.9404 - tn: 75023.3828 - tp: 72755.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m153/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9555 - auc: 0.9927 - cross entropy: 0.1131 - fn: 4655.8364 - fp: 2323.2354 - loss: 0.1131 - prc: 0.9930 - precision: 0.9696 - recall: 0.9404 - tn: 76514.3438 - tp: 74202.5859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m156/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9555 - auc: 0.9927 - cross entropy: 0.1131 - fn: 4744.3462 - fp: 2368.2500 - loss: 0.1131 - prc: 0.9930 - precision: 0.9696 - recall: 0.9404 - tn: 78005.3203 - tp: 75650.0859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m159/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9555 - auc: 0.9927 - cross entropy: 0.1130 - fn: 4832.6665 - fp: 2413.5283 - loss: 0.1130 - prc: 0.9930 - precision: 0.9696 - recall: 0.9404 - tn: 79495.2969 - tp: 77098.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m162/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0337 - accuracy: 0.9555 - auc: 0.9928 - cross entropy: 0.1130 - fn: 4920.7593 - fp: 2458.8396 - loss: 0.1130 - prc: 0.9930 - precision: 0.9696 - recall: 0.9405 - tn: 80985.6406 - tp: 78546.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m165/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9555 - auc: 0.9928 - cross entropy: 0.1130 - fn: 5008.8301 - fp: 2504.0303 - loss: 0.1130 - prc: 0.9930 - precision: 0.9696 - recall: 0.9405 - tn: 82476.1797 - tp: 79994.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m168/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9555 - auc: 0.9928 - cross entropy: 0.1130 - fn: 5096.9585 - fp: 2549.1370 - loss: 0.1130 - prc: 0.9930 - precision: 0.9696 - recall: 0.9405 - tn: 83966.5391 - tp: 81443.3594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m171/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1130 - fn: 5185.1929 - fp: 2594.1169 - loss: 0.1130 - prc: 0.9930 - precision: 0.9696 - recall: 0.9405 - tn: 85455.8750 - tp: 82892.8203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m174/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1129 - fn: 5273.3794 - fp: 2639.0173 - loss: 0.1129 - prc: 0.9930 - precision: 0.9697 - recall: 0.9406 - tn: 86945.6328 - tp: 84341.9688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m177/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1129 - fn: 5361.4858 - fp: 2683.9661 - loss: 0.1129 - prc: 0.9930 - precision: 0.9697 - recall: 0.9406 - tn: 88435.8203 - tp: 85790.7266"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m180/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1129 - fn: 5449.4668 - fp: 2729.0388 - loss: 0.1129 - prc: 0.9930 - precision: 0.9697 - recall: 0.9406 - tn: 89926.3984 - tp: 87239.0938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m183/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1129 - fn: 5537.5410 - fp: 2774.2021 - loss: 0.1129 - prc: 0.9930 - precision: 0.9697 - recall: 0.9406 - tn: 91416.2578 - tp: 88688.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m186/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1128 - fn: 5625.5591 - fp: 2819.2688 - loss: 0.1128 - prc: 0.9930 - precision: 0.9697 - recall: 0.9406 - tn: 92906.1641 - tp: 90137.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m189/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1128 - fn: 5713.4976 - fp: 2864.0688 - loss: 0.1128 - prc: 0.9930 - precision: 0.9697 - recall: 0.9407 - tn: 94396.5000 - tp: 91585.9297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m192/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1128 - fn: 5801.1929 - fp: 2909.0261 - loss: 0.1128 - prc: 0.9930 - precision: 0.9697 - recall: 0.9407 - tn: 95887.2109 - tp: 93034.5703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m195/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9556 - auc: 0.9928 - cross entropy: 0.1128 - fn: 5888.7744 - fp: 2954.1487 - loss: 0.1128 - prc: 0.9930 - precision: 0.9697 - recall: 0.9407 - tn: 97378.0312 - tp: 94483.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m198/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1128 - fn: 5976.2271 - fp: 2999.2576 - loss: 0.1128 - prc: 0.9930 - precision: 0.9697 - recall: 0.9407 - tn: 98868.0391 - tp: 95932.4766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m201/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0336 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1127 - fn: 6063.6470 - fp: 3044.5474 - loss: 0.1127 - prc: 0.9930 - precision: 0.9697 - recall: 0.9408 - tn: 100357.7734 - tp: 97382.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m204/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1127 - fn: 6151.0049 - fp: 3089.7646 - loss: 0.1127 - prc: 0.9930 - precision: 0.9697 - recall: 0.9408 - tn: 101847.5469 - tp: 98831.6875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m207/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1127 - fn: 6238.3428 - fp: 3134.9275 - loss: 0.1127 - prc: 0.9930 - precision: 0.9697 - recall: 0.9408 - tn: 103338.0469 - tp: 100280.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m210/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1127 - fn: 6325.6714 - fp: 3179.9856 - loss: 0.1127 - prc: 0.9930 - precision: 0.9697 - recall: 0.9408 - tn: 104829.1250 - tp: 101729.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m213/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1126 - fn: 6413.1128 - fp: 3225.0469 - loss: 0.1126 - prc: 0.9930 - precision: 0.9697 - recall: 0.9408 - tn: 106320.5156 - tp: 103177.3281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m216/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1126 - fn: 6500.4771 - fp: 3269.9121 - loss: 0.1126 - prc: 0.9930 - precision: 0.9697 - recall: 0.9409 - tn: 107811.9375 - tp: 104625.6719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m219/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1126 - fn: 6587.7397 - fp: 3314.7534 - loss: 0.1126 - prc: 0.9930 - precision: 0.9697 - recall: 0.9409 - tn: 109303.4922 - tp: 106074.0156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m222/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9557 - auc: 0.9928 - cross entropy: 0.1126 - fn: 6674.9277 - fp: 3359.6306 - loss: 0.1126 - prc: 0.9930 - precision: 0.9697 - recall: 0.9409 - tn: 110795.8906 - tp: 107521.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m225/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1126 - fn: 6761.8979 - fp: 3404.4399 - loss: 0.1126 - prc: 0.9930 - precision: 0.9697 - recall: 0.9409 - tn: 112289.1172 - tp: 108968.5469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m228/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1125 - fn: 6848.8901 - fp: 3449.2588 - loss: 0.1125 - prc: 0.9930 - precision: 0.9697 - recall: 0.9409 - tn: 113782.0312 - tp: 110415.8125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m231/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1125 - fn: 6935.7617 - fp: 3494.1602 - loss: 0.1125 - prc: 0.9930 - precision: 0.9697 - recall: 0.9410 - tn: 115274.5469 - tp: 111863.5312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m234/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1125 - fn: 7022.6880 - fp: 3539.0557 - loss: 0.1125 - prc: 0.9930 - precision: 0.9697 - recall: 0.9410 - tn: 116767.2188 - tp: 113311.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m237/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1125 - fn: 7109.3628 - fp: 3583.9114 - loss: 0.1125 - prc: 0.9930 - precision: 0.9697 - recall: 0.9410 - tn: 118260.4531 - tp: 114758.2734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m240/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1124 - fn: 7195.8833 - fp: 3628.7292 - loss: 0.1124 - prc: 0.9930 - precision: 0.9697 - recall: 0.9410 - tn: 119753.8281 - tp: 116205.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m243/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1124 - fn: 7282.3745 - fp: 3673.4485 - loss: 0.1124 - prc: 0.9930 - precision: 0.9697 - recall: 0.9410 - tn: 121246.9531 - tp: 117653.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m246/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0335 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1124 - fn: 7368.8862 - fp: 3718.1912 - loss: 0.1124 - prc: 0.9930 - precision: 0.9697 - recall: 0.9411 - tn: 122740.2344 - tp: 119100.6875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m249/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9558 - auc: 0.9928 - cross entropy: 0.1124 - fn: 7455.4497 - fp: 3762.8997 - loss: 0.1124 - prc: 0.9931 - precision: 0.9697 - recall: 0.9411 - tn: 124233.5000 - tp: 120548.1562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m252/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1124 - fn: 7541.9961 - fp: 3807.5317 - loss: 0.1124 - prc: 0.9931 - precision: 0.9697 - recall: 0.9411 - tn: 125727.3516 - tp: 121995.1172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m255/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1123 - fn: 7628.4155 - fp: 3851.9138 - loss: 0.1123 - prc: 0.9931 - precision: 0.9697 - recall: 0.9411 - tn: 127222.1250 - tp: 123441.5469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m258/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1123 - fn: 7714.6860 - fp: 3896.1667 - loss: 0.1123 - prc: 0.9931 - precision: 0.9697 - recall: 0.9411 - tn: 128717.1406 - tp: 124888.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m261/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1123 - fn: 7800.9385 - fp: 3940.4866 - loss: 0.1123 - prc: 0.9931 - precision: 0.9697 - recall: 0.9412 - tn: 130212.3516 - tp: 126334.2266"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m264/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1123 - fn: 7887.2046 - fp: 3984.7349 - loss: 0.1123 - prc: 0.9931 - precision: 0.9697 - recall: 0.9412 - tn: 131707.7656 - tp: 127780.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m267/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1122 - fn: 7973.4194 - fp: 4028.9214 - loss: 0.1122 - prc: 0.9931 - precision: 0.9697 - recall: 0.9412 - tn: 133202.7812 - tp: 129226.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m270/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1122 - fn: 8059.6479 - fp: 4073.0740 - loss: 0.1122 - prc: 0.9931 - precision: 0.9697 - recall: 0.9412 - tn: 134698.0781 - tp: 130673.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m273/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1122 - fn: 8145.8423 - fp: 4117.3296 - loss: 0.1122 - prc: 0.9931 - precision: 0.9697 - recall: 0.9412 - tn: 136193.6094 - tp: 132119.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m276/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9559 - auc: 0.9929 - cross entropy: 0.1122 - fn: 8232.0723 - fp: 4161.4639 - loss: 0.1122 - prc: 0.9931 - precision: 0.9697 - recall: 0.9413 - tn: 137689.6719 - tp: 133564.7812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 20ms/step - Brier score: 0.0334 - accuracy: 0.9560 - auc: 0.9929 - cross entropy: 0.1122 - fn: 8318.0391 - fp: 4205.3477 - loss: 0.1122 - prc: 0.9931 - precision: 0.9697 - recall: 0.9413 - tn: 139183.0000 - tp: 135006.2656 - val_Brier score: 0.0135 - val_accuracy: 0.9854 - val_auc: 0.9864 - val_cross entropy: 0.0582 - val_fn: 4.0000 - val_fp: 660.0000 - val_loss: 0.0582 - val_prc: 0.7222 - val_precision: 0.1057 - val_recall: 0.9512 - val_tn: 44827.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0331 - accuracy: 0.9565 - auc: 0.9924 - cross entropy: 0.1120 - fn: 58.0000 - fp: 31.0000 - loss: 0.1120 - prc: 0.9916 - precision: 0.9690 - recall: 0.9435 - tn: 991.0000 - tp: 968.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 15ms/step - Brier score: 0.0322 - accuracy: 0.9568 - auc: 0.9934 - cross entropy: 0.1067 - fn: 176.0000 - fp: 89.0000 - loss: 0.1067 - prc: 0.9931 - precision: 0.9701 - recall: 0.9428 - tn: 2977.3999 - tp: 2901.6001"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0319 - accuracy: 0.9572 - auc: 0.9935 - cross entropy: 0.1056 - fn: 264.6250 - fp: 127.8750 - loss: 0.1056 - prc: 0.9934 - precision: 0.9708 - recall: 0.9426 - tn: 4488.1250 - tp: 4335.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0316 - accuracy: 0.9576 - auc: 0.9937 - cross entropy: 0.1046 - fn: 351.3636 - fp: 165.6364 - loss: 0.1046 - prc: 0.9936 - precision: 0.9714 - recall: 0.9427 - tn: 5993.1816 - tp: 5777.8184"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 19ms/step - Brier score: 0.0316 - accuracy: 0.9577 - auc: 0.9937 - cross entropy: 0.1045 - fn: 439.1429 - fp: 206.0714 - loss: 0.1045 - prc: 0.9937 - precision: 0.9717 - recall: 0.9427 - tn: 7492.0000 - tp: 7222.7856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0316 - accuracy: 0.9578 - auc: 0.9937 - cross entropy: 0.1046 - fn: 523.7059 - fp: 247.4118 - loss: 0.1046 - prc: 0.9937 - precision: 0.9718 - recall: 0.9429 - tn: 8996.0586 - tp: 8664.8232"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0315 - accuracy: 0.9580 - auc: 0.9937 - cross entropy: 0.1047 - fn: 605.5500 - fp: 290.1500 - loss: 0.1047 - prc: 0.9937 - precision: 0.9718 - recall: 0.9432 - tn: 10500.6504 - tp: 10107.6504"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0315 - accuracy: 0.9581 - auc: 0.9937 - cross entropy: 0.1047 - fn: 687.5652 - fp: 332.3044 - loss: 0.1047 - prc: 0.9937 - precision: 0.9718 - recall: 0.9434 - tn: 12007.5215 - tp: 11548.6084"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0315 - accuracy: 0.9582 - auc: 0.9938 - cross entropy: 0.1048 - fn: 770.8077 - fp: 374.3077 - loss: 0.1048 - prc: 0.9937 - precision: 0.9718 - recall: 0.9435 - tn: 13510.9229 - tp: 12991.9619"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9583 - auc: 0.9938 - cross entropy: 0.1048 - fn: 853.4483 - fp: 416.9310 - loss: 0.1048 - prc: 0.9937 - precision: 0.9718 - recall: 0.9437 - tn: 15016.1729 - tp: 14433.4482"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9583 - auc: 0.9938 - cross entropy: 0.1048 - fn: 934.9688 - fp: 460.6875 - loss: 0.1048 - prc: 0.9937 - precision: 0.9717 - recall: 0.9438 - tn: 16521.9375 - tp: 15874.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9584 - auc: 0.9938 - cross entropy: 0.1049 - fn: 1018.4286 - fp: 504.1714 - loss: 0.1049 - prc: 0.9937 - precision: 0.9717 - recall: 0.9439 - tn: 18022.8574 - tp: 17318.5430"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0314 - accuracy: 0.9584 - auc: 0.9938 - cross entropy: 0.1050 - fn: 1101.0264 - fp: 547.1316 - loss: 0.1050 - prc: 0.9937 - precision: 0.9717 - recall: 0.9440 - tn: 19520.8418 - tp: 18767.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9584 - auc: 0.9938 - cross entropy: 0.1051 - fn: 1183.8292 - fp: 589.9756 - loss: 0.1051 - prc: 0.9937 - precision: 0.9716 - recall: 0.9441 - tn: 21013.6582 - tp: 20220.5371"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1052 - fn: 1266.5454 - fp: 634.7500 - loss: 0.1052 - prc: 0.9937 - precision: 0.9716 - recall: 0.9442 - tn: 22506.8418 - tp: 21671.8633"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1053 - fn: 1349.6809 - fp: 679.1702 - loss: 0.1053 - prc: 0.9937 - precision: 0.9715 - recall: 0.9443 - tn: 24000.5742 - tp: 23122.5742"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1054 - fn: 1431.8800 - fp: 723.5400 - loss: 0.1054 - prc: 0.9937 - precision: 0.9715 - recall: 0.9444 - tn: 25491.8594 - tp: 24576.7207"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1055 - fn: 1514.0189 - fp: 767.9434 - loss: 0.1055 - prc: 0.9937 - precision: 0.9715 - recall: 0.9444 - tn: 26983.6797 - tp: 26030.3594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1056 - fn: 1595.9108 - fp: 812.7679 - loss: 0.1056 - prc: 0.9937 - precision: 0.9714 - recall: 0.9445 - tn: 28475.2852 - tp: 27484.0352"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1056 - fn: 1677.8306 - fp: 857.6271 - loss: 0.1056 - prc: 0.9937 - precision: 0.9714 - recall: 0.9446 - tn: 29968.1348 - tp: 28936.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1057 - fn: 1760.2258 - fp: 902.5000 - loss: 0.1057 - prc: 0.9937 - precision: 0.9714 - recall: 0.9446 - tn: 31458.5332 - tp: 30390.7422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1057 - fn: 1842.7230 - fp: 947.1077 - loss: 0.1057 - prc: 0.9937 - precision: 0.9713 - recall: 0.9447 - tn: 32950.6016 - tp: 31843.5684"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9585 - auc: 0.9938 - cross entropy: 0.1058 - fn: 1925.0735 - fp: 991.5147 - loss: 0.1058 - prc: 0.9937 - precision: 0.9713 - recall: 0.9447 - tn: 34444.4688 - tp: 33294.9414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1058 - fn: 2007.3802 - fp: 1035.7887 - loss: 0.1058 - prc: 0.9937 - precision: 0.9713 - recall: 0.9448 - tn: 35938.9141 - tp: 34745.9141"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1058 - fn: 2090.2432 - fp: 1080.5135 - loss: 0.1058 - prc: 0.9937 - precision: 0.9712 - recall: 0.9448 - tn: 37433.0273 - tp: 36196.2148"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 77/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1059 - fn: 2173.1948 - fp: 1125.4026 - loss: 0.1059 - prc: 0.9937 - precision: 0.9712 - recall: 0.9449 - tn: 38927.2969 - tp: 37646.1055"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 80/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1059 - fn: 2256.4126 - fp: 1170.0500 - loss: 0.1059 - prc: 0.9937 - precision: 0.9712 - recall: 0.9449 - tn: 40421.3867 - tp: 39096.1484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 83/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1059 - fn: 2339.6868 - fp: 1214.6265 - loss: 0.1059 - prc: 0.9937 - precision: 0.9712 - recall: 0.9449 - tn: 41915.9766 - tp: 40545.7109"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 85/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2395.3765 - fp: 1244.4236 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9449 - tn: 42912.0234 - tp: 41512.1758"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 88/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2478.8635 - fp: 1288.6591 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9449 - tn: 44408.1016 - tp: 42960.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 91/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2562.2966 - fp: 1332.2638 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 45903.7578 - tp: 44409.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 94/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2645.6382 - fp: 1375.7340 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 47399.0859 - tp: 45859.5430"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 97/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2729.2063 - fp: 1418.9691 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 48895.0703 - tp: 47308.7539"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m100/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2812.8601 - fp: 1461.8600 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 50389.6016 - tp: 48759.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m103/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2896.7573 - fp: 1504.6699 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 51884.7578 - tp: 50209.8164"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m106/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 2980.7454 - fp: 1547.6132 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 53379.4531 - tp: 51660.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m109/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3064.5964 - fp: 1590.5504 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9450 - tn: 54874.7422 - tp: 53110.1094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m112/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3148.0894 - fp: 1633.2858 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9451 - tn: 56370.6172 - tp: 54560.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m115/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3231.9216 - fp: 1675.5479 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9451 - tn: 57865.9375 - tp: 56010.5898"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m118/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3316.0847 - fp: 1717.3644 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9451 - tn: 59361.5586 - tp: 57460.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m121/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3400.2480 - fp: 1759.0662 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9451 - tn: 60857.0586 - tp: 58911.6289"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m124/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3484.4033 - fp: 1800.4758 - loss: 0.1060 - prc: 0.9937 - precision: 0.9711 - recall: 0.9451 - tn: 62352.6367 - tp: 60362.4844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m127/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1060 - fn: 3568.1575 - fp: 1841.7086 - loss: 0.1060 - prc: 0.9937 - precision: 0.9712 - recall: 0.9451 - tn: 63849.2422 - tp: 61812.8906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m130/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1059 - fn: 3651.6924 - fp: 1883.3693 - loss: 0.1059 - prc: 0.9938 - precision: 0.9712 - recall: 0.9451 - tn: 65345.4688 - tp: 63263.4688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m133/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1059 - fn: 3734.8721 - fp: 1925.4962 - loss: 0.1059 - prc: 0.9938 - precision: 0.9712 - recall: 0.9451 - tn: 66842.0469 - tp: 64713.5859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m136/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9586 - auc: 0.9938 - cross entropy: 0.1059 - fn: 3817.9265 - fp: 1967.6544 - loss: 0.1059 - prc: 0.9938 - precision: 0.9712 - recall: 0.9451 - tn: 68339.5703 - tp: 66162.8438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m139/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1059 - fn: 3901.2661 - fp: 2009.6835 - loss: 0.1059 - prc: 0.9938 - precision: 0.9712 - recall: 0.9451 - tn: 69837.5625 - tp: 67611.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m142/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1059 - fn: 3984.6973 - fp: 2051.5635 - loss: 0.1059 - prc: 0.9938 - precision: 0.9712 - recall: 0.9451 - tn: 71336.6094 - tp: 69059.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m145/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1058 - fn: 4068.0137 - fp: 2093.6621 - loss: 0.1058 - prc: 0.9938 - precision: 0.9712 - recall: 0.9451 - tn: 72835.8125 - tp: 70506.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m148/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1058 - fn: 4151.3174 - fp: 2135.8987 - loss: 0.1058 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 74334.5703 - tp: 71954.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m151/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1058 - fn: 4234.5034 - fp: 2178.2385 - loss: 0.1058 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 75832.3281 - tp: 73402.9297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m154/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1058 - fn: 4317.5391 - fp: 2220.4417 - loss: 0.1058 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 77329.4062 - tp: 74852.6094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m157/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1058 - fn: 4400.4268 - fp: 2262.5159 - loss: 0.1058 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 78826.1875 - tp: 76302.8750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m160/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1058 - fn: 4483.2563 - fp: 2304.6626 - loss: 0.1058 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 80322.4219 - tp: 77753.6562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m163/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1057 - fn: 4565.9448 - fp: 2346.8835 - loss: 0.1057 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 81818.8750 - tp: 79204.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m166/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1057 - fn: 4648.5903 - fp: 2388.9639 - loss: 0.1057 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 83314.6953 - tp: 80655.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m169/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1057 - fn: 4731.2246 - fp: 2431.0415 - loss: 0.1057 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 84811.0156 - tp: 82106.7188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m172/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1057 - fn: 4813.8545 - fp: 2473.4709 - loss: 0.1057 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 86308.0547 - tp: 83556.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m175/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0314 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1057 - fn: 4896.4800 - fp: 2516.0286 - loss: 0.1057 - prc: 0.9938 - precision: 0.9712 - recall: 0.9452 - tn: 87805.0938 - tp: 85006.3906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m178/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1056 - fn: 4979.1572 - fp: 2558.4719 - loss: 0.1056 - prc: 0.9938 - precision: 0.9712 - recall: 0.9453 - tn: 89302.4141 - tp: 86455.9531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m181/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9587 - auc: 0.9938 - cross entropy: 0.1056 - fn: 5061.8398 - fp: 2600.6851 - loss: 0.1056 - prc: 0.9938 - precision: 0.9712 - recall: 0.9453 - tn: 90800.0625 - tp: 87905.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m184/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1056 - fn: 5144.5000 - fp: 2643.0381 - loss: 0.1056 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 92297.3828 - tp: 89355.0781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m187/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1056 - fn: 5227.1553 - fp: 2685.3049 - loss: 0.1056 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 93794.3359 - tp: 90805.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m190/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1056 - fn: 5309.8735 - fp: 2727.5632 - loss: 0.1056 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 95290.5859 - tp: 92255.9766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m193/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1056 - fn: 5392.4717 - fp: 2769.6943 - loss: 0.1056 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 96786.5781 - tp: 93707.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m196/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1055 - fn: 5474.9082 - fp: 2811.8164 - loss: 0.1055 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 98283.0234 - tp: 95158.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m199/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1055 - fn: 5557.4121 - fp: 2853.8643 - loss: 0.1055 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 99779.2891 - tp: 96609.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m202/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1055 - fn: 5639.7129 - fp: 2895.6882 - loss: 0.1055 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 101275.1406 - tp: 98061.4531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m205/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1055 - fn: 5721.9219 - fp: 2937.4683 - loss: 0.1055 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 102771.0547 - tp: 99513.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m208/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1055 - fn: 5804.2310 - fp: 2979.1443 - loss: 0.1055 - prc: 0.9938 - precision: 0.9713 - recall: 0.9453 - tn: 104266.5078 - tp: 100966.1172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m211/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1054 - fn: 5886.6113 - fp: 3020.7820 - loss: 0.1054 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 105762.6484 - tp: 102417.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m214/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9938 - cross entropy: 0.1054 - fn: 5968.8130 - fp: 3062.4766 - loss: 0.1054 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 107259.2812 - tp: 103869.4297"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m217/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9939 - cross entropy: 0.1054 - fn: 6051.0093 - fp: 3104.2212 - loss: 0.1054 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 108755.9688 - tp: 105320.8047"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m220/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9939 - cross entropy: 0.1054 - fn: 6133.1680 - fp: 3146.0454 - loss: 0.1054 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 110252.3203 - tp: 106772.4688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m223/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9939 - cross entropy: 0.1054 - fn: 6215.2334 - fp: 3187.9282 - loss: 0.1054 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 111748.6562 - tp: 108224.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m226/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9588 - auc: 0.9939 - cross entropy: 0.1053 - fn: 6297.1240 - fp: 3229.9514 - loss: 0.1053 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 113245.3125 - tp: 109675.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m229/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1053 - fn: 6378.9648 - fp: 3271.9390 - loss: 0.1053 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 114741.9766 - tp: 111127.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m232/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0313 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1053 - fn: 6460.6938 - fp: 3313.8447 - loss: 0.1053 - prc: 0.9938 - precision: 0.9713 - recall: 0.9454 - tn: 116238.5000 - tp: 112578.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m235/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1053 - fn: 6542.3701 - fp: 3355.7915 - loss: 0.1053 - prc: 0.9939 - precision: 0.9713 - recall: 0.9454 - tn: 117734.7812 - tp: 114031.0547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m238/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1053 - fn: 6623.9116 - fp: 3397.7898 - loss: 0.1053 - prc: 0.9939 - precision: 0.9713 - recall: 0.9454 - tn: 119230.9609 - tp: 115483.3359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m241/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1053 - fn: 6705.4316 - fp: 3439.7261 - loss: 0.1053 - prc: 0.9939 - precision: 0.9713 - recall: 0.9455 - tn: 120726.7969 - tp: 116936.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m244/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 6786.8853 - fp: 3481.6475 - loss: 0.1052 - prc: 0.9939 - precision: 0.9713 - recall: 0.9455 - tn: 122222.7109 - tp: 118388.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m247/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 6868.3481 - fp: 3523.6155 - loss: 0.1052 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 123719.0391 - tp: 119841.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m250/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 6949.8599 - fp: 3565.5759 - loss: 0.1052 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 125215.1719 - tp: 121293.3984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m253/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 7031.5415 - fp: 3607.5850 - loss: 0.1052 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 126711.3594 - tp: 122745.5156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m256/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 7113.4492 - fp: 3649.6523 - loss: 0.1052 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 128207.0859 - tp: 124197.8125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m259/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 7195.3052 - fp: 3691.8647 - loss: 0.1052 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 129702.5625 - tp: 125650.2734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m262/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1052 - fn: 7277.3511 - fp: 3734.0076 - loss: 0.1052 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 131198.0781 - tp: 127102.5547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m265/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1051 - fn: 7359.3096 - fp: 3776.1284 - loss: 0.1051 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 132693.4531 - tp: 128555.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m268/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1051 - fn: 7441.1304 - fp: 3818.1941 - loss: 0.1051 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 134188.8281 - tp: 130007.8438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m271/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1051 - fn: 7522.9004 - fp: 3860.1255 - loss: 0.1051 - prc: 0.9939 - precision: 0.9714 - recall: 0.9455 - tn: 135684.3281 - tp: 131460.6406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m274/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1051 - fn: 7604.6787 - fp: 3902.0730 - loss: 0.1051 - prc: 0.9939 - precision: 0.9714 - recall: 0.9456 - tn: 137179.5938 - tp: 132913.6562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m277/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9589 - auc: 0.9939 - cross entropy: 0.1051 - fn: 7686.3682 - fp: 3944.0793 - loss: 0.1051 - prc: 0.9939 - precision: 0.9714 - recall: 0.9456 - tn: 138674.2500 - tp: 134367.3125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 20ms/step - Brier score: 0.0312 - accuracy: 0.9590 - auc: 0.9939 - cross entropy: 0.1051 - fn: 7740.6382 - fp: 3971.9570 - loss: 0.1051 - prc: 0.9939 - precision: 0.9714 - recall: 0.9456 - tn: 139666.8906 - tp: 135333.1719 - val_Brier score: 0.0125 - val_accuracy: 0.9862 - val_auc: 0.9868 - val_cross entropy: 0.0532 - val_fn: 4.0000 - val_fp: 624.0000 - val_loss: 0.0532 - val_prc: 0.7229 - val_precision: 0.1111 - val_recall: 0.9512 - val_tn: 44863.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 8/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - Brier score: 0.0294 - accuracy: 0.9619 - auc: 0.9952 - cross entropy: 0.0982 - fn: 59.0000 - fp: 19.0000 - loss: 0.0982 - prc: 0.9952 - precision: 0.9801 - recall: 0.9408 - tn: 1033.0000 - tp: 937.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 16ms/step - Brier score: 0.0297 - accuracy: 0.9613 - auc: 0.9948 - cross entropy: 0.1014 - fn: 170.2000 - fp: 67.2000 - loss: 0.1014 - prc: 0.9948 - precision: 0.9779 - recall: 0.9436 - tn: 3011.3999 - tp: 2895.2000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0298 - accuracy: 0.9611 - auc: 0.9947 - cross entropy: 0.1022 - fn: 249.3750 - fp: 110.0000 - loss: 0.1022 - prc: 0.9945 - precision: 0.9764 - recall: 0.9447 - tn: 4511.5000 - tp: 4345.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0298 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1019 - fn: 323.9091 - fp: 151.6364 - loss: 0.1019 - prc: 0.9945 - precision: 0.9756 - recall: 0.9458 - tn: 6015.1816 - tp: 5797.2729"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0297 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1014 - fn: 400.0000 - fp: 192.2143 - loss: 0.1014 - prc: 0.9946 - precision: 0.9752 - recall: 0.9464 - tn: 7522.5713 - tp: 7245.2144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1010 - fn: 478.7059 - fp: 231.5882 - loss: 0.1010 - prc: 0.9946 - precision: 0.9749 - recall: 0.9467 - tn: 9027.8232 - tp: 8693.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1009 - fn: 557.9000 - fp: 271.5500 - loss: 0.1009 - prc: 0.9946 - precision: 0.9747 - recall: 0.9469 - tn: 10528.4502 - tp: 10146.0996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1007 - fn: 636.7391 - fp: 311.7826 - loss: 0.1007 - prc: 0.9946 - precision: 0.9746 - recall: 0.9471 - tn: 12018.0000 - tp: 11609.4785"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1007 - fn: 716.2692 - fp: 352.3077 - loss: 0.1007 - prc: 0.9946 - precision: 0.9745 - recall: 0.9472 - tn: 13506.0000 - tp: 13073.4229"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1006 - fn: 795.4138 - fp: 393.3103 - loss: 0.1006 - prc: 0.9946 - precision: 0.9743 - recall: 0.9473 - tn: 15000.2412 - tp: 14531.0342"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1006 - fn: 874.3125 - fp: 434.0625 - loss: 0.1006 - prc: 0.9946 - precision: 0.9742 - recall: 0.9474 - tn: 16499.4375 - tp: 15984.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1006 - fn: 953.0000 - fp: 475.0571 - loss: 0.1006 - prc: 0.9946 - precision: 0.9741 - recall: 0.9475 - tn: 17999.4277 - tp: 17436.5137"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1006 - fn: 1031.2368 - fp: 516.4474 - loss: 0.1006 - prc: 0.9946 - precision: 0.9740 - recall: 0.9476 - tn: 19496.8691 - tp: 18891.4473"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1006 - fn: 1108.6342 - fp: 557.0488 - loss: 0.1006 - prc: 0.9946 - precision: 0.9739 - recall: 0.9477 - tn: 20997.0723 - tp: 20345.2441"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1005 - fn: 1186.2727 - fp: 596.6136 - loss: 0.1005 - prc: 0.9946 - precision: 0.9739 - recall: 0.9478 - tn: 22497.0918 - tp: 21800.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1004 - fn: 1263.7021 - fp: 636.5958 - loss: 0.1004 - prc: 0.9946 - precision: 0.9739 - recall: 0.9478 - tn: 23998.0215 - tp: 23253.6816"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1004 - fn: 1341.5200 - fp: 677.2200 - loss: 0.1004 - prc: 0.9946 - precision: 0.9738 - recall: 0.9479 - tn: 25495.5801 - tp: 24709.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1003 - fn: 1418.7358 - fp: 717.9056 - loss: 0.1003 - prc: 0.9946 - precision: 0.9738 - recall: 0.9480 - tn: 26992.4727 - tp: 26166.8867"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.1003 - fn: 1495.8036 - fp: 758.7143 - loss: 0.1003 - prc: 0.9946 - precision: 0.9737 - recall: 0.9480 - tn: 28492.0723 - tp: 27621.4102"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1002 - fn: 1572.4916 - fp: 798.8813 - loss: 0.1002 - prc: 0.9946 - precision: 0.9737 - recall: 0.9481 - tn: 29992.3047 - tp: 29076.3223"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1002 - fn: 1649.2258 - fp: 838.9355 - loss: 0.1002 - prc: 0.9946 - precision: 0.9737 - recall: 0.9482 - tn: 31489.7266 - tp: 30534.1133"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1001 - fn: 1726.2307 - fp: 879.3692 - loss: 0.1001 - prc: 0.9946 - precision: 0.9737 - recall: 0.9482 - tn: 32984.1250 - tp: 31994.2773"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1001 - fn: 1803.8235 - fp: 920.3530 - loss: 0.1001 - prc: 0.9946 - precision: 0.9736 - recall: 0.9483 - tn: 34476.6172 - tp: 33455.2070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0296 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1001 - fn: 1881.5352 - fp: 961.5493 - loss: 0.1001 - prc: 0.9946 - precision: 0.9736 - recall: 0.9483 - tn: 35969.7617 - tp: 34915.1562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1000 - fn: 1959.4459 - fp: 1002.3514 - loss: 0.1000 - prc: 0.9946 - precision: 0.9736 - recall: 0.9483 - tn: 37462.5664 - tp: 36375.6367"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 77/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1000 - fn: 2037.6884 - fp: 1043.0129 - loss: 0.1000 - prc: 0.9946 - precision: 0.9736 - recall: 0.9484 - tn: 38954.3750 - tp: 37836.9219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 80/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.1000 - fn: 2116.1626 - fp: 1084.1000 - loss: 0.1000 - prc: 0.9946 - precision: 0.9735 - recall: 0.9484 - tn: 40448.2109 - tp: 39295.5234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 83/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2194.5181 - fp: 1124.7952 - loss: 0.0999 - prc: 0.9946 - precision: 0.9735 - recall: 0.9484 - tn: 41942.1914 - tp: 40754.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 86/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2273.2441 - fp: 1165.3954 - loss: 0.0999 - prc: 0.9946 - precision: 0.9735 - recall: 0.9484 - tn: 43435.9648 - tp: 42213.3945"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 89/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2351.6628 - fp: 1206.2921 - loss: 0.0999 - prc: 0.9946 - precision: 0.9735 - recall: 0.9484 - tn: 44930.6406 - tp: 43671.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 91/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2403.8132 - fp: 1233.6263 - loss: 0.0999 - prc: 0.9946 - precision: 0.9735 - recall: 0.9484 - tn: 45926.6250 - tp: 44643.9336"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 94/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2482.1597 - fp: 1274.7554 - loss: 0.0999 - prc: 0.9946 - precision: 0.9734 - recall: 0.9485 - tn: 47417.8828 - tp: 46105.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 97/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2560.8145 - fp: 1315.6598 - loss: 0.0999 - prc: 0.9946 - precision: 0.9734 - recall: 0.9485 - tn: 48908.8125 - tp: 47566.7109"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m100/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2639.4500 - fp: 1356.9399 - loss: 0.0999 - prc: 0.9946 - precision: 0.9734 - recall: 0.9485 - tn: 50399.9883 - tp: 49027.6211"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m103/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2717.8835 - fp: 1398.3689 - loss: 0.0999 - prc: 0.9946 - precision: 0.9734 - recall: 0.9485 - tn: 51892.3125 - tp: 50487.4375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m106/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2796.2642 - fp: 1439.4717 - loss: 0.0999 - prc: 0.9946 - precision: 0.9734 - recall: 0.9485 - tn: 53384.9609 - tp: 51947.3008"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m109/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2874.6147 - fp: 1480.4679 - loss: 0.0999 - prc: 0.9946 - precision: 0.9734 - recall: 0.9485 - tn: 54877.6055 - tp: 53407.3125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m112/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 2952.8750 - fp: 1521.5536 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9485 - tn: 56370.3672 - tp: 54867.2070"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m115/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3031.0608 - fp: 1562.7478 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 57863.6797 - tp: 56326.5117"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m118/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3109.2795 - fp: 1603.8390 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 59357.9922 - tp: 57784.8906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m121/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3187.8018 - fp: 1644.7107 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 60851.8594 - tp: 59243.6289"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m124/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3266.3628 - fp: 1685.4113 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 62345.2031 - tp: 60703.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m127/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3345.0708 - fp: 1725.7638 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 63838.4102 - tp: 62162.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m130/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3423.5847 - fp: 1765.7384 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 65332.3320 - tp: 63622.3477"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m133/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3502.0225 - fp: 1805.8270 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 66826.1250 - tp: 65082.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m136/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3580.0000 - fp: 1845.9117 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 68321.4062 - tp: 66540.6875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m139/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3657.9136 - fp: 1886.2446 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 69817.4141 - tp: 67998.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m142/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3735.7253 - fp: 1927.0282 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9486 - tn: 71312.8906 - tp: 69456.3594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m145/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0999 - fn: 3813.5518 - fp: 1967.7449 - loss: 0.0999 - prc: 0.9946 - precision: 0.9733 - recall: 0.9487 - tn: 72808.0312 - tp: 70914.6719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m148/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0998 - fn: 3891.1892 - fp: 2008.3987 - loss: 0.0998 - prc: 0.9946 - precision: 0.9733 - recall: 0.9487 - tn: 74303.4062 - tp: 72373.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m151/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0998 - fn: 3968.8809 - fp: 2048.7815 - loss: 0.0998 - prc: 0.9946 - precision: 0.9733 - recall: 0.9487 - tn: 75798.7500 - tp: 73831.5859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m154/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4046.5520 - fp: 2089.2207 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 77294.0078 - tp: 75290.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m157/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9613 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4124.1401 - fp: 2129.6433 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 78789.2031 - tp: 76749.0156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m160/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4201.7876 - fp: 2169.8999 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 80283.8203 - tp: 78208.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m163/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4279.4170 - fp: 2210.1719 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 81778.0859 - tp: 79668.3281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m166/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4356.7046 - fp: 2250.5481 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 83272.5391 - tp: 81128.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m169/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4434.0415 - fp: 2290.9585 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 84766.7656 - tp: 82588.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m172/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4511.4185 - fp: 2331.5349 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9487 - tn: 86261.9453 - tp: 84047.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m175/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4588.6284 - fp: 2372.1714 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 87758.1797 - tp: 85505.0156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m178/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4665.8706 - fp: 2412.7585 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 89255.4531 - tp: 86961.9141"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m181/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0295 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0998 - fn: 4743.1050 - fp: 2453.3425 - loss: 0.0998 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 90752.3359 - tp: 88419.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m184/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 4820.4780 - fp: 2493.7554 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 92249.7422 - tp: 89876.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m187/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 4898.0000 - fp: 2534.0535 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 93747.5312 - tp: 91332.4141"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m190/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 4975.5210 - fp: 2574.4473 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 95245.6719 - tp: 92788.3594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m193/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 5052.9688 - fp: 2614.5647 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 96743.4375 - tp: 94245.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m196/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 5130.5308 - fp: 2654.5562 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 98239.8750 - tp: 95703.0391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m199/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 5208.0503 - fp: 2694.5479 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 99736.1875 - tp: 97161.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m202/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 5285.4058 - fp: 2734.6831 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 101232.6719 - tp: 98619.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m205/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 5362.5171 - fp: 2775.0879 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9488 - tn: 102729.3359 - tp: 100077.0547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m208/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0997 - fn: 5439.6299 - fp: 2815.5239 - loss: 0.0997 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 104225.5547 - tp: 101535.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m211/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5516.5640 - fp: 2855.8247 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 105721.2656 - tp: 102994.3438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m214/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5593.4160 - fp: 2896.0327 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 107217.3203 - tp: 104453.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m217/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5670.0137 - fp: 2936.2903 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 108713.5547 - tp: 105912.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m220/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5746.7363 - fp: 2976.6045 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 110210.1797 - tp: 107370.4844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m223/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5823.3901 - fp: 3016.8296 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 111706.2656 - tp: 108829.5156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m226/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5899.9072 - fp: 3057.1238 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 113202.5625 - tp: 110288.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m229/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 5976.3667 - fp: 3097.3450 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 114699.3438 - tp: 111746.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m232/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0996 - fn: 6052.6123 - fp: 3137.4482 - loss: 0.0996 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 116195.6953 - tp: 113206.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m235/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6128.8340 - fp: 3177.5190 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9489 - tn: 117692.1953 - tp: 114665.4531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m238/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6205.1050 - fp: 3217.6890 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 119189.1016 - tp: 116124.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m241/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6281.3940 - fp: 3257.8713 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 120686.4922 - tp: 117582.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m244/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6357.6519 - fp: 3298.0000 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 122183.7734 - tp: 119040.5703"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m247/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9614 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6433.9839 - fp: 3338.1174 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 123681.2734 - tp: 120498.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m250/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6510.4399 - fp: 3378.2161 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 125179.5000 - tp: 121955.8438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m253/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0995 - fn: 6586.9014 - fp: 3418.1384 - loss: 0.0995 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 126677.0547 - tp: 123413.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m256/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 6663.4102 - fp: 3458.1367 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 128174.2500 - tp: 124872.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m259/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 6739.8301 - fp: 3498.2703 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 129671.6797 - tp: 126330.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m262/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 6816.1221 - fp: 3538.2329 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 131168.5156 - tp: 127789.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m265/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 6892.3662 - fp: 3578.2000 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9490 - tn: 132665.3438 - tp: 129248.0859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m268/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0294 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 6968.5894 - fp: 3618.1157 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9491 - tn: 134162.5469 - tp: 130706.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m271/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0293 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 7044.8008 - fp: 3657.9558 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9491 - tn: 135659.6406 - tp: 132165.5938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m274/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0293 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0994 - fn: 7121.0073 - fp: 3697.7446 - loss: 0.0994 - prc: 0.9946 - precision: 0.9732 - recall: 0.9491 - tn: 137156.1094 - tp: 133625.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m277/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0293 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0993 - fn: 7197.3213 - fp: 3737.5596 - loss: 0.0993 - prc: 0.9946 - precision: 0.9732 - recall: 0.9491 - tn: 138652.5312 - tp: 135084.5938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0293 - accuracy: 0.9615 - auc: 0.9947 - cross entropy: 0.0993 - fn: 7248.0288 - fp: 3764.0574 - loss: 0.0993 - prc: 0.9946 - precision: 0.9732 - recall: 0.9491 - tn: 139646.4844 - tp: 136054.0938 - val_Brier score: 0.0117 - val_accuracy: 0.9867 - val_auc: 0.9866 - val_cross entropy: 0.0492 - val_fn: 4.0000 - val_fp: 603.0000 - val_loss: 0.0492 - val_prc: 0.7255 - val_precision: 0.1145 - val_recall: 0.9512 - val_tn: 44884.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0266 - accuracy: 0.9658 - auc: 0.9958 - cross entropy: 0.0892 - fn: 42.0000 - fp: 28.0000 - loss: 0.0892 - prc: 0.9962 - precision: 0.9726 - recall: 0.9595 - tn: 983.0000 - tp: 995.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 19ms/step - Brier score: 0.0282 - accuracy: 0.9630 - auc: 0.9951 - cross entropy: 0.0966 - fn: 118.5000 - fp: 74.7500 - loss: 0.0966 - prc: 0.9952 - precision: 0.9710 - recall: 0.9555 - tn: 2450.7500 - tp: 2476.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9625 - auc: 0.9949 - cross entropy: 0.0986 - fn: 197.4286 - fp: 113.7143 - loss: 0.0986 - prc: 0.9949 - precision: 0.9718 - recall: 0.9537 - tn: 3933.8572 - tp: 3947.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 10/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 22ms/step - Brier score: 0.0289 - accuracy: 0.9623 - auc: 0.9948 - cross entropy: 0.0994 - fn: 276.7000 - fp: 153.0000 - loss: 0.0994 - prc: 0.9948 - precision: 0.9721 - recall: 0.9526 - tn: 5428.5000 - tp: 5405.7998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 13/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 22ms/step - Brier score: 0.0289 - accuracy: 0.9622 - auc: 0.9948 - cross entropy: 0.0997 - fn: 354.3077 - fp: 191.6154 - loss: 0.0997 - prc: 0.9947 - precision: 0.9724 - recall: 0.9521 - tn: 6921.2310 - tp: 6868.8462"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 16/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 23ms/step - Brier score: 0.0289 - accuracy: 0.9623 - auc: 0.9948 - cross entropy: 0.0997 - fn: 429.5625 - fp: 229.6875 - loss: 0.0997 - prc: 0.9947 - precision: 0.9727 - recall: 0.9519 - tn: 8421.0000 - tp: 8327.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 18/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m6s\u001b[0m 23ms/step - Brier score: 0.0289 - accuracy: 0.9623 - auc: 0.9948 - cross entropy: 0.0995 - fn: 479.1111 - fp: 256.2778 - loss: 0.0995 - prc: 0.9948 - precision: 0.9727 - recall: 0.9518 - tn: 9422.2773 - tp: 9298.3330"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 21/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 23ms/step - Brier score: 0.0288 - accuracy: 0.9622 - auc: 0.9948 - cross entropy: 0.0994 - fn: 553.9048 - fp: 298.9048 - loss: 0.0994 - prc: 0.9947 - precision: 0.9727 - recall: 0.9517 - tn: 10925.2861 - tp: 10749.9043"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 23ms/step - Brier score: 0.0288 - accuracy: 0.9623 - auc: 0.9949 - cross entropy: 0.0993 - fn: 602.8696 - fp: 326.5652 - loss: 0.0993 - prc: 0.9947 - precision: 0.9727 - recall: 0.9517 - tn: 11928.5215 - tp: 11718.0439"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 24ms/step - Brier score: 0.0288 - accuracy: 0.9622 - auc: 0.9949 - cross entropy: 0.0992 - fn: 676.8077 - fp: 369.0769 - loss: 0.0992 - prc: 0.9947 - precision: 0.9726 - recall: 0.9517 - tn: 13428.3076 - tp: 13173.8076"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 23ms/step - Brier score: 0.0288 - accuracy: 0.9622 - auc: 0.9949 - cross entropy: 0.0991 - fn: 752.0000 - fp: 411.2758 - loss: 0.0991 - prc: 0.9947 - precision: 0.9726 - recall: 0.9516 - tn: 14925.7930 - tp: 14630.9307"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 23ms/step - Brier score: 0.0288 - accuracy: 0.9622 - auc: 0.9949 - cross entropy: 0.0990 - fn: 826.9375 - fp: 452.7812 - loss: 0.0990 - prc: 0.9947 - precision: 0.9726 - recall: 0.9515 - tn: 16420.6562 - tp: 16091.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 23ms/step - Brier score: 0.0288 - accuracy: 0.9622 - auc: 0.9949 - cross entropy: 0.0989 - fn: 902.1429 - fp: 494.3429 - loss: 0.0989 - prc: 0.9947 - precision: 0.9726 - recall: 0.9515 - tn: 17913.8281 - tp: 17553.6855"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 22ms/step - Brier score: 0.0288 - accuracy: 0.9622 - auc: 0.9949 - cross entropy: 0.0988 - fn: 977.8421 - fp: 536.0526 - loss: 0.0988 - prc: 0.9947 - precision: 0.9726 - recall: 0.9515 - tn: 19401.4473 - tp: 19020.6582"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 22ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0988 - fn: 1055.0000 - fp: 577.1464 - loss: 0.0988 - prc: 0.9947 - precision: 0.9726 - recall: 0.9514 - tn: 20888.3906 - tp: 20487.4629"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 22ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0987 - fn: 1133.0454 - fp: 617.1591 - loss: 0.0987 - prc: 0.9947 - precision: 0.9726 - recall: 0.9513 - tn: 22374.6816 - tp: 21955.1133"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m5s\u001b[0m 22ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0986 - fn: 1210.8085 - fp: 656.1915 - loss: 0.0986 - prc: 0.9947 - precision: 0.9726 - recall: 0.9513 - tn: 23864.0215 - tp: 23420.9785"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0985 - fn: 1288.0000 - fp: 694.6000 - loss: 0.0985 - prc: 0.9947 - precision: 0.9727 - recall: 0.9512 - tn: 25355.3008 - tp: 24886.0996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 22ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0984 - fn: 1365.2075 - fp: 733.3962 - loss: 0.0984 - prc: 0.9947 - precision: 0.9728 - recall: 0.9512 - tn: 26848.9805 - tp: 26348.4160"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0983 - fn: 1443.0358 - fp: 772.1250 - loss: 0.0983 - prc: 0.9947 - precision: 0.9728 - recall: 0.9511 - tn: 28343.8926 - tp: 27808.9473"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0982 - fn: 1520.5084 - fp: 811.0000 - loss: 0.0982 - prc: 0.9947 - precision: 0.9728 - recall: 0.9510 - tn: 29837.6777 - tp: 29270.8145"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0288 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0981 - fn: 1597.8710 - fp: 850.3549 - loss: 0.0981 - prc: 0.9948 - precision: 0.9729 - recall: 0.9510 - tn: 31331.3379 - tp: 30732.4355"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0981 - fn: 1675.0769 - fp: 889.6923 - loss: 0.0981 - prc: 0.9948 - precision: 0.9729 - recall: 0.9510 - tn: 32825.4141 - tp: 32193.8145"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0980 - fn: 1752.4412 - fp: 928.7647 - loss: 0.0980 - prc: 0.9948 - precision: 0.9729 - recall: 0.9509 - tn: 34316.8984 - tp: 33657.8984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0979 - fn: 1829.3944 - fp: 968.0986 - loss: 0.0979 - prc: 0.9948 - precision: 0.9729 - recall: 0.9509 - tn: 35809.8164 - tp: 35120.6914"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0979 - fn: 1906.1351 - fp: 1007.3243 - loss: 0.0979 - prc: 0.9948 - precision: 0.9730 - recall: 0.9509 - tn: 37303.7852 - tp: 36582.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 77/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0978 - fn: 1982.8312 - fp: 1046.3376 - loss: 0.0978 - prc: 0.9948 - precision: 0.9730 - recall: 0.9509 - tn: 38797.2852 - tp: 38045.5469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 80/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0977 - fn: 2059.6875 - fp: 1084.5500 - loss: 0.0977 - prc: 0.9948 - precision: 0.9730 - recall: 0.9508 - tn: 40291.9609 - tp: 39507.8008"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 83/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9621 - auc: 0.9949 - cross entropy: 0.0976 - fn: 2136.0361 - fp: 1122.0482 - loss: 0.0976 - prc: 0.9948 - precision: 0.9731 - recall: 0.9508 - tn: 41787.3359 - tp: 40970.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 86/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9622 - auc: 0.9949 - cross entropy: 0.0976 - fn: 2212.1511 - fp: 1159.2791 - loss: 0.0976 - prc: 0.9948 - precision: 0.9731 - recall: 0.9508 - tn: 43282.9883 - tp: 42433.5820"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 89/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0287 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0975 - fn: 2287.9888 - fp: 1197.1011 - loss: 0.0975 - prc: 0.9948 - precision: 0.9731 - recall: 0.9508 - tn: 44777.1367 - tp: 43897.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 92/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0286 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0975 - fn: 2363.8696 - fp: 1235.2065 - loss: 0.0975 - prc: 0.9948 - precision: 0.9732 - recall: 0.9508 - tn: 46269.4258 - tp: 45363.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 95/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0286 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0974 - fn: 2439.3894 - fp: 1273.4421 - loss: 0.0974 - prc: 0.9948 - precision: 0.9732 - recall: 0.9508 - tn: 47761.2539 - tp: 46829.9141"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 98/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0286 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0973 - fn: 2514.9897 - fp: 1311.5510 - loss: 0.0973 - prc: 0.9948 - precision: 0.9732 - recall: 0.9508 - tn: 49253.6641 - tp: 48295.7969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m101/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 21ms/step - Brier score: 0.0286 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0973 - fn: 2590.6335 - fp: 1349.7426 - loss: 0.0973 - prc: 0.9948 - precision: 0.9733 - recall: 0.9508 - tn: 50747.4062 - tp: 49760.2188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m104/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0286 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0972 - fn: 2666.2595 - fp: 1387.8557 - loss: 0.0972 - prc: 0.9948 - precision: 0.9733 - recall: 0.9508 - tn: 52241.6250 - tp: 51224.2578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m107/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0286 - accuracy: 0.9622 - auc: 0.9950 - cross entropy: 0.0972 - fn: 2742.1775 - fp: 1425.6168 - loss: 0.0972 - prc: 0.9948 - precision: 0.9733 - recall: 0.9508 - tn: 53738.0078 - tp: 52686.1953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m110/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0286 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0971 - fn: 2818.0637 - fp: 1463.3818 - loss: 0.0971 - prc: 0.9948 - precision: 0.9733 - recall: 0.9508 - tn: 55234.9375 - tp: 54147.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m113/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0286 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0970 - fn: 2893.7434 - fp: 1501.3363 - loss: 0.0970 - prc: 0.9948 - precision: 0.9734 - recall: 0.9508 - tn: 56731.7266 - tp: 55609.1953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m116/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0970 - fn: 2969.5000 - fp: 1539.5603 - loss: 0.0970 - prc: 0.9948 - precision: 0.9734 - recall: 0.9508 - tn: 58226.6719 - tp: 57072.2656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m119/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0970 - fn: 3045.2437 - fp: 1577.7059 - loss: 0.0970 - prc: 0.9948 - precision: 0.9734 - recall: 0.9508 - tn: 59721.6133 - tp: 58535.4375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m122/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0969 - fn: 3120.7048 - fp: 1615.8606 - loss: 0.0969 - prc: 0.9949 - precision: 0.9734 - recall: 0.9508 - tn: 61216.0820 - tp: 59999.3516"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m125/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0969 - fn: 3196.0559 - fp: 1653.9520 - loss: 0.0969 - prc: 0.9949 - precision: 0.9734 - recall: 0.9508 - tn: 62710.2383 - tp: 61463.7539"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m128/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0968 - fn: 3271.3125 - fp: 1692.1641 - loss: 0.0968 - prc: 0.9949 - precision: 0.9734 - recall: 0.9508 - tn: 64205.4219 - tp: 62927.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m131/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0968 - fn: 3346.3281 - fp: 1730.3282 - loss: 0.0968 - prc: 0.9949 - precision: 0.9735 - recall: 0.9508 - tn: 65701.3438 - tp: 64390.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m134/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9623 - auc: 0.9950 - cross entropy: 0.0967 - fn: 3420.9180 - fp: 1768.3209 - loss: 0.0967 - prc: 0.9949 - precision: 0.9735 - recall: 0.9508 - tn: 67197.6875 - tp: 65853.0781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m137/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9624 - auc: 0.9950 - cross entropy: 0.0967 - fn: 3495.0803 - fp: 1806.3065 - loss: 0.0967 - prc: 0.9949 - precision: 0.9735 - recall: 0.9508 - tn: 68694.7344 - tp: 67315.8750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m140/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9624 - auc: 0.9950 - cross entropy: 0.0966 - fn: 3568.9072 - fp: 1844.1357 - loss: 0.0966 - prc: 0.9949 - precision: 0.9735 - recall: 0.9508 - tn: 70193.0938 - tp: 68777.8672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m143/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0285 - accuracy: 0.9624 - auc: 0.9950 - cross entropy: 0.0966 - fn: 3642.5176 - fp: 1881.8462 - loss: 0.0966 - prc: 0.9949 - precision: 0.9735 - recall: 0.9508 - tn: 71692.1328 - tp: 70239.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m146/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9624 - auc: 0.9950 - cross entropy: 0.0965 - fn: 3716.0137 - fp: 1919.5890 - loss: 0.0965 - prc: 0.9949 - precision: 0.9736 - recall: 0.9508 - tn: 73190.8594 - tp: 71701.5312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m149/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9624 - auc: 0.9951 - cross entropy: 0.0965 - fn: 3789.6309 - fp: 1957.4094 - loss: 0.0965 - prc: 0.9949 - precision: 0.9736 - recall: 0.9508 - tn: 74688.9844 - tp: 73163.9766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m152/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9624 - auc: 0.9951 - cross entropy: 0.0964 - fn: 3863.2434 - fp: 1995.3816 - loss: 0.0964 - prc: 0.9949 - precision: 0.9736 - recall: 0.9508 - tn: 76186.8438 - tp: 74626.5312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m155/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9624 - auc: 0.9951 - cross entropy: 0.0964 - fn: 3936.8130 - fp: 2033.5935 - loss: 0.0964 - prc: 0.9949 - precision: 0.9736 - recall: 0.9509 - tn: 77685.2812 - tp: 76088.3125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m158/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0964 - fn: 4010.4114 - fp: 2071.9683 - loss: 0.0964 - prc: 0.9949 - precision: 0.9736 - recall: 0.9509 - tn: 79182.8672 - tp: 77550.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m161/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0963 - fn: 4084.0808 - fp: 2110.3354 - loss: 0.0963 - prc: 0.9949 - precision: 0.9736 - recall: 0.9509 - tn: 80680.6797 - tp: 79012.9062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m164/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0963 - fn: 4157.8291 - fp: 2148.8171 - loss: 0.0963 - prc: 0.9949 - precision: 0.9736 - recall: 0.9509 - tn: 82177.8359 - tp: 80475.5156"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m167/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0963 - fn: 4231.4673 - fp: 2187.3594 - loss: 0.0963 - prc: 0.9949 - precision: 0.9736 - recall: 0.9509 - tn: 83674.2969 - tp: 81938.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m170/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0962 - fn: 4304.7705 - fp: 2226.1470 - loss: 0.0962 - prc: 0.9949 - precision: 0.9736 - recall: 0.9509 - tn: 85170.7344 - tp: 83402.3438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m173/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0962 - fn: 4377.7979 - fp: 2264.8787 - loss: 0.0962 - prc: 0.9949 - precision: 0.9737 - recall: 0.9509 - tn: 86666.4375 - tp: 84866.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m176/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 20ms/step - Brier score: 0.0284 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0962 - fn: 4450.7271 - fp: 2303.5000 - loss: 0.0962 - prc: 0.9949 - precision: 0.9737 - recall: 0.9509 - tn: 88162.3984 - tp: 86331.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m179/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0961 - fn: 4523.8379 - fp: 2341.9050 - loss: 0.0961 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 89658.7344 - tp: 87795.5234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m182/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9625 - auc: 0.9951 - cross entropy: 0.0961 - fn: 4596.8130 - fp: 2380.1868 - loss: 0.0961 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 91154.8828 - tp: 89260.1172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m185/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0960 - fn: 4669.7188 - fp: 2418.4866 - loss: 0.0960 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 92650.7109 - tp: 90725.0859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m188/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0960 - fn: 4742.3989 - fp: 2456.8723 - loss: 0.0960 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 94146.9922 - tp: 92189.7344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m191/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0960 - fn: 4814.8481 - fp: 2495.1990 - loss: 0.0960 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 95644.3750 - tp: 93653.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m194/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0959 - fn: 4887.1289 - fp: 2533.2527 - loss: 0.0959 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 97142.9688 - tp: 95116.6484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m197/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0959 - fn: 4959.1978 - fp: 2571.3655 - loss: 0.0959 - prc: 0.9949 - precision: 0.9737 - recall: 0.9510 - tn: 98641.1797 - tp: 96580.2578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m200/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0959 - fn: 5031.1348 - fp: 2609.5100 - loss: 0.0959 - prc: 0.9950 - precision: 0.9737 - recall: 0.9511 - tn: 100139.2734 - tp: 98044.0781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m203/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0958 - fn: 5103.0591 - fp: 2647.6306 - loss: 0.0958 - prc: 0.9950 - precision: 0.9737 - recall: 0.9511 - tn: 101637.2656 - tp: 99508.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m206/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9626 - auc: 0.9951 - cross entropy: 0.0958 - fn: 5175.0391 - fp: 2685.7815 - loss: 0.0958 - prc: 0.9950 - precision: 0.9738 - recall: 0.9511 - tn: 103134.5469 - tp: 100972.6328"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m209/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0283 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0958 - fn: 5246.9141 - fp: 2723.8660 - loss: 0.0958 - prc: 0.9950 - precision: 0.9738 - recall: 0.9511 - tn: 104632.0156 - tp: 102437.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m212/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0957 - fn: 5318.6602 - fp: 2761.9622 - loss: 0.0957 - prc: 0.9950 - precision: 0.9738 - recall: 0.9511 - tn: 106129.0391 - tp: 103902.3359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m215/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0957 - fn: 5390.1812 - fp: 2800.1396 - loss: 0.0957 - prc: 0.9950 - precision: 0.9738 - recall: 0.9511 - tn: 107626.4297 - tp: 105367.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m218/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0957 - fn: 5461.7109 - fp: 2838.3992 - loss: 0.0957 - prc: 0.9950 - precision: 0.9738 - recall: 0.9512 - tn: 109124.1406 - tp: 106831.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m221/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0956 - fn: 5533.3120 - fp: 2876.7827 - loss: 0.0956 - prc: 0.9950 - precision: 0.9738 - recall: 0.9512 - tn: 110622.1406 - tp: 108295.7656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m224/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0956 - fn: 5604.9600 - fp: 2915.1741 - loss: 0.0956 - prc: 0.9950 - precision: 0.9738 - recall: 0.9512 - tn: 112120.4453 - tp: 109759.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m227/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9951 - cross entropy: 0.0956 - fn: 5676.4141 - fp: 2953.4934 - loss: 0.0956 - prc: 0.9950 - precision: 0.9738 - recall: 0.9512 - tn: 113619.0938 - tp: 111222.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m230/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9627 - auc: 0.9952 - cross entropy: 0.0955 - fn: 5748.1216 - fp: 2991.9521 - loss: 0.0955 - prc: 0.9950 - precision: 0.9738 - recall: 0.9512 - tn: 115118.2891 - tp: 112685.6406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m233/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0955 - fn: 5819.7769 - fp: 3030.4636 - loss: 0.0955 - prc: 0.9950 - precision: 0.9738 - recall: 0.9512 - tn: 116617.3750 - tp: 114148.3828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m236/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0955 - fn: 5891.4111 - fp: 3068.8008 - loss: 0.0955 - prc: 0.9950 - precision: 0.9738 - recall: 0.9513 - tn: 118116.5391 - tp: 115611.2422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m239/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0954 - fn: 5963.0127 - fp: 3107.1089 - loss: 0.0954 - prc: 0.9950 - precision: 0.9738 - recall: 0.9513 - tn: 119615.4062 - tp: 117074.4688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m242/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0954 - fn: 6034.5205 - fp: 3145.3635 - loss: 0.0954 - prc: 0.9950 - precision: 0.9738 - recall: 0.9513 - tn: 121115.2812 - tp: 118536.8359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m245/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0954 - fn: 6106.0449 - fp: 3183.4980 - loss: 0.0954 - prc: 0.9950 - precision: 0.9738 - recall: 0.9513 - tn: 122614.8125 - tp: 119999.6484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m248/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0282 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0954 - fn: 6177.6289 - fp: 3221.6372 - loss: 0.0954 - prc: 0.9950 - precision: 0.9739 - recall: 0.9513 - tn: 124114.3828 - tp: 121462.3516"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m251/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0953 - fn: 6249.4102 - fp: 3259.7808 - loss: 0.0953 - prc: 0.9950 - precision: 0.9739 - recall: 0.9513 - tn: 125613.3047 - tp: 122925.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m254/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0953 - fn: 6321.2324 - fp: 3297.9526 - loss: 0.0953 - prc: 0.9950 - precision: 0.9739 - recall: 0.9513 - tn: 127112.1484 - tp: 124388.6719"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m257/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9628 - auc: 0.9952 - cross entropy: 0.0953 - fn: 6393.1401 - fp: 3336.1633 - loss: 0.0953 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 128611.0781 - tp: 125851.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m260/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0953 - fn: 6465.0425 - fp: 3374.3999 - loss: 0.0953 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 130110.0312 - tp: 127314.5234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m263/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0952 - fn: 6536.9199 - fp: 3412.7756 - loss: 0.0952 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 131609.4219 - tp: 128776.8906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m266/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0952 - fn: 6608.7520 - fp: 3451.0640 - loss: 0.0952 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 133109.0156 - tp: 130239.1641"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m269/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0952 - fn: 6680.4570 - fp: 3489.4609 - loss: 0.0952 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 134608.3438 - tp: 131701.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m272/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0952 - fn: 6752.0918 - fp: 3527.8345 - loss: 0.0952 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 136107.5938 - tp: 133164.4844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m275/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0951 - fn: 6823.6548 - fp: 3566.2910 - loss: 0.0951 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 137607.2344 - tp: 134626.8125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0951 - fn: 6895.1260 - fp: 3604.7627 - loss: 0.0951 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 139106.9844 - tp: 136089.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 20ms/step - Brier score: 0.0281 - accuracy: 0.9629 - auc: 0.9952 - cross entropy: 0.0951 - fn: 6918.7705 - fp: 3617.4875 - loss: 0.0951 - prc: 0.9950 - precision: 0.9739 - recall: 0.9514 - tn: 139603.3438 - tp: 136573.0625 - val_Brier score: 0.0106 - val_accuracy: 0.9879 - val_auc: 0.9863 - val_cross entropy: 0.0447 - val_fn: 4.0000 - val_fp: 549.0000 - val_loss: 0.0447 - val_prc: 0.7313 - val_precision: 0.1244 - val_recall: 0.9512 - val_tn: 44938.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 10/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - Brier score: 0.0247 - accuracy: 0.9697 - auc: 0.9968 - cross entropy: 0.0825 - fn: 47.0000 - fp: 15.0000 - loss: 0.0825 - prc: 0.9969 - precision: 0.9850 - recall: 0.9546 - tn: 998.0000 - tp: 988.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 16ms/step - Brier score: 0.0263 - accuracy: 0.9673 - auc: 0.9959 - cross entropy: 0.0890 - fn: 134.2000 - fp: 71.0000 - loss: 0.0890 - prc: 0.9958 - precision: 0.9784 - recall: 0.9561 - tn: 2977.3999 - tp: 2961.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0267 - accuracy: 0.9665 - auc: 0.9957 - cross entropy: 0.0904 - fn: 201.1250 - fp: 114.2500 - loss: 0.0904 - prc: 0.9956 - precision: 0.9767 - recall: 0.9563 - tn: 4464.0000 - tp: 4436.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0268 - accuracy: 0.9660 - auc: 0.9957 - cross entropy: 0.0908 - fn: 269.9091 - fp: 156.0909 - loss: 0.0908 - prc: 0.9955 - precision: 0.9758 - recall: 0.9562 - tn: 5960.0000 - tp: 5902.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0269 - accuracy: 0.9657 - auc: 0.9956 - cross entropy: 0.0908 - fn: 340.2857 - fp: 196.9286 - loss: 0.0908 - prc: 0.9955 - precision: 0.9753 - recall: 0.9560 - tn: 7446.7856 - tp: 7376.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0269 - accuracy: 0.9655 - auc: 0.9956 - cross entropy: 0.0907 - fn: 409.4706 - fp: 236.3529 - loss: 0.0907 - prc: 0.9955 - precision: 0.9751 - recall: 0.9559 - tn: 8938.1768 - tp: 8848.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0269 - accuracy: 0.9655 - auc: 0.9956 - cross entropy: 0.0907 - fn: 478.7000 - fp: 275.1000 - loss: 0.0907 - prc: 0.9955 - precision: 0.9749 - recall: 0.9558 - tn: 10431.5498 - tp: 10318.6504"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0269 - accuracy: 0.9654 - auc: 0.9956 - cross entropy: 0.0906 - fn: 548.3913 - fp: 313.5217 - loss: 0.0906 - prc: 0.9955 - precision: 0.9749 - recall: 0.9557 - tn: 11923.3916 - tp: 11790.6953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0269 - accuracy: 0.9653 - auc: 0.9956 - cross entropy: 0.0905 - fn: 618.5385 - fp: 350.3077 - loss: 0.0905 - prc: 0.9955 - precision: 0.9749 - recall: 0.9557 - tn: 13414.0771 - tp: 13265.0771"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0269 - accuracy: 0.9653 - auc: 0.9956 - cross entropy: 0.0904 - fn: 690.2759 - fp: 386.0690 - loss: 0.0904 - prc: 0.9955 - precision: 0.9749 - recall: 0.9555 - tn: 14909.4141 - tp: 14734.2412"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0268 - accuracy: 0.9653 - auc: 0.9956 - cross entropy: 0.0903 - fn: 760.4688 - fp: 420.9688 - loss: 0.0903 - prc: 0.9955 - precision: 0.9750 - recall: 0.9554 - tn: 16414.0938 - tp: 16196.4688"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0268 - accuracy: 0.9653 - auc: 0.9957 - cross entropy: 0.0902 - fn: 829.5714 - fp: 455.7714 - loss: 0.0902 - prc: 0.9955 - precision: 0.9750 - recall: 0.9554 - tn: 17916.6562 - tp: 17662.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0268 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0902 - fn: 898.7632 - fp: 491.3421 - loss: 0.0902 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 19415.0000 - tp: 19130.8945"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0268 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0901 - fn: 967.0488 - fp: 527.1464 - loss: 0.0901 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 20910.5371 - tp: 20603.2676"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0901 - fn: 1035.8636 - fp: 563.7045 - loss: 0.0901 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 22404.1816 - tp: 22076.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0901 - fn: 1104.4894 - fp: 601.0000 - loss: 0.0901 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 23895.7012 - tp: 23550.8086"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0901 - fn: 1173.1801 - fp: 638.8600 - loss: 0.0901 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 25387.2207 - tp: 25024.7402"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0900 - fn: 1242.0189 - fp: 677.2642 - loss: 0.0900 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 26879.8672 - tp: 26496.8496"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0900 - fn: 1310.5892 - fp: 715.4286 - loss: 0.0900 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 28371.6426 - tp: 27970.3398"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0900 - fn: 1379.1017 - fp: 753.2034 - loss: 0.0900 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 29863.1191 - tp: 29444.5762"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0900 - fn: 1447.4193 - fp: 790.4839 - loss: 0.0900 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 31354.9844 - tp: 30919.1133"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 64/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0900 - fn: 1492.7812 - fp: 815.3281 - loss: 0.0900 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 32349.3125 - tp: 31902.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 67/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0900 - fn: 1560.5522 - fp: 852.9105 - loss: 0.0900 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 33844.2383 - tp: 33374.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 70/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 1628.5143 - fp: 890.8571 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 35340.5859 - tp: 34844.0430"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 73/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 1696.6849 - fp: 928.6439 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 36836.7266 - tp: 36313.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 76/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 1765.0790 - fp: 966.3289 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 38331.9492 - tp: 37784.6445"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 79/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 1833.3418 - fp: 1004.1772 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 39828.4414 - tp: 39254.0391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 82/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 1901.6342 - fp: 1042.1097 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 41324.2305 - tp: 40724.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 85/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 1969.9294 - fp: 1079.6941 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 42818.7656 - tp: 42195.6133"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 88/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2037.7500 - fp: 1117.1023 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 44314.6602 - tp: 43666.4883"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 91/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2104.8572 - fp: 1155.2197 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9554 - tn: 45810.4727 - tp: 45137.4492"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 94/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2171.6702 - fp: 1193.5212 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9555 - tn: 47305.1289 - tp: 46609.6797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 97/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2238.6804 - fp: 1231.5464 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9555 - tn: 48800.6172 - tp: 48081.1562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m100/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2305.5801 - fp: 1269.6000 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9555 - tn: 50296.3398 - tp: 49552.4805"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m103/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2372.6311 - fp: 1307.8446 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9555 - tn: 51790.5625 - tp: 51024.9609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m106/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2439.4905 - fp: 1345.8490 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9555 - tn: 53285.6133 - tp: 52497.0469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m109/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2506.1194 - fp: 1383.6973 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9555 - tn: 54781.0352 - tp: 53969.1484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m112/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9654 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2572.6072 - fp: 1421.4375 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9556 - tn: 56277.5000 - tp: 55440.4570"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m115/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0267 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2638.8435 - fp: 1459.3739 - loss: 0.0899 - prc: 0.9955 - precision: 0.9751 - recall: 0.9556 - tn: 57774.3203 - tp: 56911.4609"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m118/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2705.1526 - fp: 1497.2627 - loss: 0.0899 - prc: 0.9955 - precision: 0.9750 - recall: 0.9556 - tn: 59270.9844 - tp: 58382.6016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m121/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 2771.3967 - fp: 1535.1074 - loss: 0.0899 - prc: 0.9955 - precision: 0.9750 - recall: 0.9556 - tn: 60767.2305 - tp: 59854.2656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m124/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 2837.4839 - fp: 1572.8951 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9556 - tn: 62263.5664 - tp: 61326.0547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m127/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 2903.8188 - fp: 1610.6614 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 63760.7383 - tp: 62796.7812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m130/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 2970.4153 - fp: 1648.6538 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 65258.0703 - tp: 64266.8633"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m133/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 3037.0225 - fp: 1686.6616 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 66755.6172 - tp: 65736.7031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m136/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 3103.6692 - fp: 1724.6396 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 68252.4141 - tp: 67207.2812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m139/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 3170.5251 - fp: 1762.7266 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 69749.1641 - tp: 68677.5859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m142/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3237.5422 - fp: 1800.9578 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 71246.7656 - tp: 70146.7344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m145/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3304.7173 - fp: 1838.9104 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 72744.0469 - tp: 71616.3203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m148/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3371.9392 - fp: 1876.9595 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 74240.3438 - tp: 73086.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m151/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3439.2649 - fp: 1915.3842 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 75736.1953 - tp: 74557.1484"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m154/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3506.7014 - fp: 1953.8636 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 77232.1172 - tp: 76027.3203"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m157/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3574.0764 - fp: 1992.4268 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 78728.1406 - tp: 77497.3594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m160/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3641.6812 - fp: 2031.0375 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9557 - tn: 80224.7344 - tp: 78966.5469"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m163/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3709.3191 - fp: 2069.6626 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 81721.3281 - tp: 80435.6953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m166/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3776.9758 - fp: 2108.1687 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 83218.5469 - tp: 81904.3047"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m169/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3844.5088 - fp: 2146.4851 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 84717.2031 - tp: 83371.8047"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m172/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0899 - fn: 3912.0291 - fp: 2184.9827 - loss: 0.0899 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 86215.2578 - tp: 84839.7266"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m175/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 3979.6057 - fp: 2223.3257 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 87713.5391 - tp: 86307.5312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m178/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4047.2642 - fp: 2261.4775 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 89211.6719 - tp: 87775.5859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m181/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4114.9004 - fp: 2299.4143 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 90710.3125 - tp: 89243.3672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m184/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4182.5654 - fp: 2337.3206 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 92209.1094 - tp: 90711.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m187/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4250.1978 - fp: 2375.1550 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 93707.9297 - tp: 92178.7188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m190/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4317.7524 - fp: 2412.8894 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 95207.0391 - tp: 93646.3125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m193/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4385.0879 - fp: 2450.6838 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 96707.1250 - tp: 95113.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m196/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4452.1431 - fp: 2488.5664 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 98207.5547 - tp: 96579.7344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m199/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4519.1006 - fp: 2526.5125 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 99707.6250 - tp: 98046.7656"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m202/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4586.0889 - fp: 2564.3464 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 101208.2812 - tp: 99513.2812"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m205/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9655 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4653.0098 - fp: 2602.0488 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 102708.8125 - tp: 100980.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m208/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4719.7163 - fp: 2639.6394 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 104209.2031 - tp: 102447.4375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m211/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0898 - fn: 4786.4121 - fp: 2677.2939 - loss: 0.0898 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 105709.1641 - tp: 103915.1328"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m214/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 4853.2241 - fp: 2714.9861 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 107209.9531 - tp: 105381.8359"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m217/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 4920.0781 - fp: 2752.7559 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 108710.0703 - tp: 106849.0938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m220/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 4986.8545 - fp: 2790.5364 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9558 - tn: 110210.0469 - tp: 108316.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m223/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5053.4932 - fp: 2828.3811 - loss: 0.0897 - prc: 0.9954 - precision: 0.9749 - recall: 0.9558 - tn: 111710.1172 - tp: 109784.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m226/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5119.9868 - fp: 2866.1592 - loss: 0.0897 - prc: 0.9954 - precision: 0.9749 - recall: 0.9558 - tn: 113209.7656 - tp: 111252.0859"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m229/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5186.5063 - fp: 2903.7773 - loss: 0.0897 - prc: 0.9954 - precision: 0.9749 - recall: 0.9559 - tn: 114710.0938 - tp: 112719.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m232/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5252.9526 - fp: 2941.3318 - loss: 0.0897 - prc: 0.9954 - precision: 0.9749 - recall: 0.9559 - tn: 116210.6797 - tp: 114187.0391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m235/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5319.3872 - fp: 2978.7361 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9559 - tn: 117711.1172 - tp: 115654.7578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m238/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5385.7773 - fp: 3016.1135 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9559 - tn: 119211.8047 - tp: 117122.3047"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m241/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5452.3154 - fp: 3053.5933 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9559 - tn: 120712.5000 - tp: 118589.5938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m244/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0266 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5518.7378 - fp: 3091.1311 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9559 - tn: 122213.2891 - tp: 120056.8438"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m247/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5585.3481 - fp: 3128.8826 - loss: 0.0897 - prc: 0.9954 - precision: 0.9750 - recall: 0.9559 - tn: 123713.2500 - tp: 121524.5234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m250/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0897 - fn: 5652.1040 - fp: 3166.6001 - loss: 0.0897 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 125212.4922 - tp: 122992.7969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m253/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 5718.8101 - fp: 3204.2766 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 126712.1406 - tp: 124460.7734"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m256/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 5785.4531 - fp: 3242.0391 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 128211.7812 - tp: 125928.7188"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m259/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 5852.0889 - fp: 3279.7336 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 129711.2266 - tp: 127396.9531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m262/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 5918.9009 - fp: 3317.4084 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 131210.2969 - tp: 128865.3906"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m265/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 5985.7773 - fp: 3355.1509 - loss: 0.0896 - prc: 0.9955 - precision: 0.9749 - recall: 0.9559 - tn: 132709.4844 - tp: 130333.5938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m268/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 6052.7949 - fp: 3392.7910 - loss: 0.0896 - prc: 0.9955 - precision: 0.9749 - recall: 0.9559 - tn: 134208.9688 - tp: 131801.4531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m271/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 6119.9482 - fp: 3430.3652 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 135708.9375 - tp: 133268.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m274/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 6187.1494 - fp: 3467.9927 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 137208.9844 - tp: 134735.8750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m277/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 6254.2349 - fp: 3505.6318 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 138709.0000 - tp: 136203.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 20ms/step - Brier score: 0.0265 - accuracy: 0.9656 - auc: 0.9957 - cross entropy: 0.0896 - fn: 6298.8350 - fp: 3530.5591 - loss: 0.0896 - prc: 0.9955 - precision: 0.9750 - recall: 0.9559 - tn: 139705.2344 - tp: 137178.0312 - val_Brier score: 0.0099 - val_accuracy: 0.9886 - val_auc: 0.9820 - val_cross entropy: 0.0413 - val_fn: 4.0000 - val_fp: 515.0000 - val_loss: 0.0413 - val_prc: 0.7090 - val_precision: 0.1315 - val_recall: 0.9512 - val_tn: 44972.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 11/100\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 4ms/step - Brier score: 0.0266 - accuracy: 0.9648 - auc: 0.9952 - cross entropy: 0.0919 - fn: 46.0000 - fp: 26.0000 - loss: 0.0919 - prc: 0.9947 - precision: 0.9742 - recall: 0.9553 - tn: 993.0000 - tp: 983.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 15ms/step - Brier score: 0.0259 - accuracy: 0.9673 - auc: 0.9957 - cross entropy: 0.0876 - fn: 134.2000 - fp: 64.0000 - loss: 0.0876 - prc: 0.9953 - precision: 0.9779 - recall: 0.9555 - tn: 3047.0000 - tp: 2898.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0257 - accuracy: 0.9676 - auc: 0.9958 - cross entropy: 0.0872 - fn: 200.5000 - fp: 95.3750 - loss: 0.0872 - prc: 0.9955 - precision: 0.9783 - recall: 0.9559 - tn: 4541.8750 - tp: 4378.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 11/278\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 17ms/step - Brier score: 0.0256 - accuracy: 0.9676 - auc: 0.9958 - cross entropy: 0.0869 - fn: 266.2727 - fp: 129.1818 - loss: 0.0869 - prc: 0.9955 - precision: 0.9783 - recall: 0.9562 - tn: 6031.0000 - tp: 5861.5454"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 14/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 18ms/step - Brier score: 0.0255 - accuracy: 0.9677 - auc: 0.9958 - cross entropy: 0.0870 - fn: 329.2143 - fp: 164.7143 - loss: 0.0870 - prc: 0.9956 - precision: 0.9781 - recall: 0.9565 - tn: 7525.3569 - tp: 7340.7144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 17/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0255 - accuracy: 0.9677 - auc: 0.9959 - cross entropy: 0.0869 - fn: 390.5294 - fp: 200.8824 - loss: 0.0869 - prc: 0.9956 - precision: 0.9779 - recall: 0.9569 - tn: 9018.4121 - tp: 8822.1768"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 20/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0254 - accuracy: 0.9678 - auc: 0.9959 - cross entropy: 0.0867 - fn: 452.7000 - fp: 234.6500 - loss: 0.0867 - prc: 0.9956 - precision: 0.9779 - recall: 0.9572 - tn: 10510.0498 - tp: 10306.5996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 23/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9959 - cross entropy: 0.0866 - fn: 515.8696 - fp: 268.1739 - loss: 0.0866 - prc: 0.9957 - precision: 0.9779 - recall: 0.9574 - tn: 12002.6953 - tp: 11789.2607"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 26/278\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0864 - fn: 579.5769 - fp: 301.1538 - loss: 0.0864 - prc: 0.9957 - precision: 0.9779 - recall: 0.9575 - tn: 13494.4229 - tp: 13272.8457"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 29/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0864 - fn: 644.0690 - fp: 335.4138 - loss: 0.0864 - prc: 0.9957 - precision: 0.9779 - recall: 0.9576 - tn: 14984.3789 - tp: 14756.1377"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 32/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0863 - fn: 708.0312 - fp: 369.7812 - loss: 0.0863 - prc: 0.9957 - precision: 0.9778 - recall: 0.9577 - tn: 16476.1875 - tp: 16238.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 35/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0862 - fn: 770.8000 - fp: 404.0571 - loss: 0.0862 - prc: 0.9957 - precision: 0.9778 - recall: 0.9578 - tn: 17976.0000 - tp: 17713.1426"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 38/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0252 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0862 - fn: 832.8947 - fp: 439.1053 - loss: 0.0862 - prc: 0.9957 - precision: 0.9778 - recall: 0.9578 - tn: 19479.8164 - tp: 19184.1836"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 41/278\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0252 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0862 - fn: 895.8781 - fp: 474.6342 - loss: 0.0862 - prc: 0.9957 - precision: 0.9777 - recall: 0.9579 - tn: 20987.5859 - tp: 20649.9023"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 44/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0252 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0861 - fn: 958.8864 - fp: 510.5000 - loss: 0.0861 - prc: 0.9957 - precision: 0.9776 - recall: 0.9579 - tn: 22496.8184 - tp: 22113.7949"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 47/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0252 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0861 - fn: 1021.5958 - fp: 546.9787 - loss: 0.0861 - prc: 0.9957 - precision: 0.9776 - recall: 0.9580 - tn: 24002.8945 - tp: 23580.5312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 50/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0252 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0861 - fn: 1084.2400 - fp: 583.2800 - loss: 0.0861 - prc: 0.9957 - precision: 0.9775 - recall: 0.9580 - tn: 25507.0996 - tp: 25049.3809"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 53/278\u001b[0m \u001b[32m━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0252 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0861 - fn: 1147.1510 - fp: 619.6981 - loss: 0.0861 - prc: 0.9957 - precision: 0.9775 - recall: 0.9581 - tn: 27011.8496 - tp: 26517.3027"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 56/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9680 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1210.8214 - fp: 656.9107 - loss: 0.0862 - prc: 0.9957 - precision: 0.9774 - recall: 0.9581 - tn: 28516.9473 - tp: 27983.3223"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 59/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1274.9491 - fp: 693.5593 - loss: 0.0862 - prc: 0.9957 - precision: 0.9773 - recall: 0.9581 - tn: 30021.0684 - tp: 29450.4238"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 62/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1339.5483 - fp: 729.9677 - loss: 0.0862 - prc: 0.9957 - precision: 0.9773 - recall: 0.9581 - tn: 31523.2266 - tp: 30919.2578"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 65/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1403.9385 - fp: 766.4308 - loss: 0.0862 - prc: 0.9957 - precision: 0.9772 - recall: 0.9581 - tn: 33026.9375 - tp: 32386.6914"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 68/278\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m4s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1468.5588 - fp: 803.0588 - loss: 0.0862 - prc: 0.9957 - precision: 0.9772 - recall: 0.9581 - tn: 34528.9414 - tp: 33855.4414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 71/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1533.0140 - fp: 840.1268 - loss: 0.0862 - prc: 0.9957 - precision: 0.9772 - recall: 0.9581 - tn: 36031.0273 - tp: 35323.8320"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 74/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9679 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1597.0946 - fp: 876.8649 - loss: 0.0862 - prc: 0.9957 - precision: 0.9771 - recall: 0.9581 - tn: 37534.7148 - tp: 36791.3242"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 77/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1660.6104 - fp: 913.4286 - loss: 0.0862 - prc: 0.9957 - precision: 0.9771 - recall: 0.9581 - tn: 39037.2227 - tp: 38260.7422"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 80/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1724.3375 - fp: 949.5500 - loss: 0.0862 - prc: 0.9957 - precision: 0.9770 - recall: 0.9582 - tn: 40540.5391 - tp: 39729.5742"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 83/278\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1787.9639 - fp: 985.6265 - loss: 0.0862 - prc: 0.9957 - precision: 0.9770 - recall: 0.9582 - tn: 42045.3359 - tp: 41197.0742"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 86/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1851.2559 - fp: 1022.1395 - loss: 0.0862 - prc: 0.9957 - precision: 0.9770 - recall: 0.9582 - tn: 43549.2539 - tp: 42665.3477"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 89/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1914.4832 - fp: 1058.7416 - loss: 0.0862 - prc: 0.9957 - precision: 0.9770 - recall: 0.9582 - tn: 45053.8320 - tp: 44132.9453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 92/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 1977.8152 - fp: 1095.2500 - loss: 0.0862 - prc: 0.9957 - precision: 0.9769 - recall: 0.9582 - tn: 46557.8789 - tp: 45601.0547"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 95/278\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2041.1790 - fp: 1131.9263 - loss: 0.0862 - prc: 0.9957 - precision: 0.9769 - recall: 0.9582 - tn: 48062.3359 - tp: 47068.5586"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 98/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2104.4897 - fp: 1168.3062 - loss: 0.0862 - prc: 0.9957 - precision: 0.9769 - recall: 0.9582 - tn: 49568.1445 - tp: 48535.0625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m101/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2168.0891 - fp: 1204.5149 - loss: 0.0862 - prc: 0.9957 - precision: 0.9769 - recall: 0.9582 - tn: 51072.9219 - tp: 50002.4766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m104/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2231.3364 - fp: 1240.8077 - loss: 0.0862 - prc: 0.9957 - precision: 0.9768 - recall: 0.9582 - tn: 52578.3281 - tp: 51469.5273"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m107/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2294.3831 - fp: 1277.0281 - loss: 0.0862 - prc: 0.9957 - precision: 0.9768 - recall: 0.9582 - tn: 54083.1016 - tp: 52937.4844"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m110/278\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2357.5000 - fp: 1313.5000 - loss: 0.0862 - prc: 0.9957 - precision: 0.9768 - recall: 0.9583 - tn: 55587.9375 - tp: 54405.0625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m113/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2420.4514 - fp: 1350.0088 - loss: 0.0862 - prc: 0.9957 - precision: 0.9768 - recall: 0.9583 - tn: 57092.0000 - tp: 55873.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m116/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0862 - fn: 2483.3535 - fp: 1386.7672 - loss: 0.0862 - prc: 0.9957 - precision: 0.9768 - recall: 0.9583 - tn: 58595.8203 - tp: 57342.0586"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m119/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m3s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2546.3613 - fp: 1423.3025 - loss: 0.0861 - prc: 0.9957 - precision: 0.9768 - recall: 0.9583 - tn: 60099.3008 - tp: 58811.0352"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m122/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2609.3032 - fp: 1459.9426 - loss: 0.0861 - prc: 0.9957 - precision: 0.9767 - recall: 0.9583 - tn: 61603.5742 - tp: 60279.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m125/278\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2672.4800 - fp: 1496.5439 - loss: 0.0861 - prc: 0.9957 - precision: 0.9767 - recall: 0.9583 - tn: 63108.4805 - tp: 61746.4961"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m128/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2735.3984 - fp: 1533.1953 - loss: 0.0861 - prc: 0.9957 - precision: 0.9767 - recall: 0.9583 - tn: 64613.8125 - tp: 63213.5938"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m131/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2798.6794 - fp: 1569.9313 - loss: 0.0861 - prc: 0.9957 - precision: 0.9767 - recall: 0.9583 - tn: 66118.0781 - tp: 64681.3125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m134/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9678 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2862.1121 - fp: 1606.7687 - loss: 0.0861 - prc: 0.9957 - precision: 0.9767 - recall: 0.9583 - tn: 67621.6719 - tp: 66149.4453"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m137/278\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2925.4963 - fp: 1643.6788 - loss: 0.0861 - prc: 0.9957 - precision: 0.9766 - recall: 0.9583 - tn: 69124.7031 - tp: 67618.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m140/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0861 - fn: 2988.6001 - fp: 1680.4071 - loss: 0.0861 - prc: 0.9957 - precision: 0.9766 - recall: 0.9583 - tn: 70627.4844 - tp: 69087.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m143/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0861 - fn: 3051.2656 - fp: 1717.1328 - loss: 0.0861 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 72130.5938 - tp: 70557.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m146/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3113.8013 - fp: 1753.7466 - loss: 0.0860 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 73633.8750 - tp: 72026.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m149/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3176.2080 - fp: 1790.0604 - loss: 0.0860 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 75137.5391 - tp: 73496.1953"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m152/278\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3238.6973 - fp: 1826.1514 - loss: 0.0860 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 76641.1172 - tp: 74966.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m155/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3301.1484 - fp: 1862.3354 - loss: 0.0860 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 78144.5391 - tp: 76435.9766"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m158/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3363.6963 - fp: 1898.6836 - loss: 0.0860 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 79648.2656 - tp: 77905.3516"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m161/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3426.2422 - fp: 1934.9131 - loss: 0.0860 - prc: 0.9957 - precision: 0.9766 - recall: 0.9584 - tn: 81151.4922 - tp: 79375.3516"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m164/278\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3488.9573 - fp: 1970.8658 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9584 - tn: 82654.6328 - tp: 80845.5391"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m167/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3551.9700 - fp: 2006.7366 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9584 - tn: 84157.7188 - tp: 82315.5781"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m170/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3615.2117 - fp: 2042.7118 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9584 - tn: 85660.8906 - tp: 83785.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m173/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m2s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3678.3643 - fp: 2078.7456 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9584 - tn: 87162.7109 - tp: 85256.1797"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m176/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3741.5740 - fp: 2114.7898 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9584 - tn: 88664.6016 - tp: 86727.0312"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m179/278\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3804.7429 - fp: 2150.8547 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9584 - tn: 90166.9531 - tp: 88197.4531"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m182/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0860 - fn: 3867.8955 - fp: 2186.9065 - loss: 0.0860 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 91670.0625 - tp: 89667.1406"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m185/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 3930.8918 - fp: 2222.9243 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 93173.1172 - tp: 91137.0625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m188/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 3993.9626 - fp: 2259.0320 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 94676.7734 - tp: 92606.2344"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m191/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4057.0315 - fp: 2295.1624 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 96179.6016 - tp: 94076.2031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m194/278\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4120.0874 - fp: 2331.2422 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 97682.7578 - tp: 95545.9141"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m197/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4183.1221 - fp: 2367.3096 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 99185.7422 - tp: 97015.8281"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m200/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4246.1650 - fp: 2403.4299 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 100688.2734 - tp: 98486.1328"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m203/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4309.2905 - fp: 2439.4531 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 102190.8438 - tp: 99956.4062"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m206/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4372.5630 - fp: 2475.5630 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 103693.0078 - tp: 101426.8672"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m209/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4435.8755 - fp: 2511.7463 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 105194.8672 - tp: 102897.5078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m212/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4499.2168 - fp: 2547.9199 - loss: 0.0859 - prc: 0.9957 - precision: 0.9765 - recall: 0.9585 - tn: 106696.8750 - tp: 104367.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m215/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4562.5396 - fp: 2584.0930 - loss: 0.0859 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 108199.3750 - tp: 105837.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m217/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4604.7510 - fp: 2608.2166 - loss: 0.0859 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 109201.0391 - tp: 106817.9922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m220/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4668.0820 - fp: 2644.4226 - loss: 0.0859 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 110703.3906 - tp: 108288.1016"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m223/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 19ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0859 - fn: 4731.3003 - fp: 2680.6995 - loss: 0.0859 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 112206.1953 - tp: 109757.8047"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m226/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m1s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 4794.4956 - fp: 2716.9646 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 113710.1172 - tp: 111226.4219"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m229/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 4857.8862 - fp: 2753.1616 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 115213.4609 - tp: 112695.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m232/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 4921.3276 - fp: 2789.3621 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 116716.8203 - tp: 114164.4922"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m235/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 4984.8384 - fp: 2825.6382 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 118220.1484 - tp: 115633.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m238/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5048.4287 - fp: 2861.8696 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 119722.8047 - tp: 117102.8984"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m241/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5112.0952 - fp: 2898.1868 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 121224.7109 - tp: 118573.0078"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m244/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5175.7949 - fp: 2934.4795 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 122726.4297 - tp: 120043.2969"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m247/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5239.4697 - fp: 2970.6802 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 124228.1875 - tp: 121513.6562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m250/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5302.9360 - fp: 3006.8799 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 125730.4844 - tp: 122983.7031"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m253/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5366.2251 - fp: 3043.0396 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 127233.0234 - tp: 124453.7109"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m256/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5429.4336 - fp: 3079.2500 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 128735.7031 - tp: 125923.6172"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m259/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5492.8457 - fp: 3115.4324 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 130238.1562 - tp: 127393.5625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m262/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5556.3818 - fp: 3151.5076 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 131740.0938 - tp: 128864.0234"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m265/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5619.8301 - fp: 3187.5659 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 133242.0000 - tp: 130334.6094"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m267/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5662.1387 - fp: 3211.6143 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 134243.0938 - tp: 131315.1562"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m270/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5725.6631 - fp: 3247.6592 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 135744.8281 - tp: 132785.8594"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m273/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0858 - fn: 5789.2017 - fp: 3283.7363 - loss: 0.0858 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 137247.0000 - tp: 134256.0625"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m276/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0857 - fn: 5852.7280 - fp: 3319.8188 - loss: 0.0857 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 138748.7031 - tp: 135726.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m278/278\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 20ms/step - Brier score: 0.0253 - accuracy: 0.9677 - auc: 0.9960 - cross entropy: 0.0857 - fn: 5916.1006 - fp: 3355.8567 - loss: 0.0857 - prc: 0.9957 - precision: 0.9764 - recall: 0.9585 - tn: 140246.7344 - tp: 137193.9531 - val_Brier score: 0.0093 - val_accuracy: 0.9894 - val_auc: 0.9822 - val_cross entropy: 0.0385 - val_fn: 5.0000 - val_fp: 476.0000 - val_loss: 0.0385 - val_prc: 0.7162 - val_precision: 0.1392 - val_recall: 0.9390 - val_tn: 45011.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 11: early stopping\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Restoring model weights from the end of the best epoch: 1.\n"
]
}
],
"source": [
"resampled_model = make_model()\n",
"resampled_model.load_weights(initial_weights)\n",
"\n",
"# Reset the bias to zero, since this dataset is balanced.\n",
"output_layer = resampled_model.layers[-1]\n",
"output_layer.bias.assign([0])\n",
"\n",
"val_ds = tf.data.Dataset.from_tensor_slices((val_features, val_labels)).cache()\n",
"val_ds = val_ds.batch(BATCH_SIZE).prefetch(2)\n",
"\n",
"resampled_history = resampled_model.fit(\n",
" resampled_ds,\n",
" epochs=EPOCHS,\n",
" steps_per_epoch=resampled_steps_per_epoch,\n",
" callbacks=[early_stopping()],\n",
" validation_data=val_ds)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "avALvzUp3T_c"
},
"source": [
"If the training process were considering the whole dataset on each gradient update, this oversampling would be basically identical to the class weighting.\n",
"\n",
"But when training the model batch-wise, as you did here, the oversampled data provides a smoother gradient signal: Instead of each positive example being shown in one batch with a large weight, they're shown in many different batches each time with a small weight.\n",
"\n",
"This smoother gradient signal makes it easier to train the model."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "klHZ0HV76VC5"
},
"source": [
"### Check training history\n",
"\n",
"Note that the distributions of metrics will be different here, because the training data has a totally different distribution from the validation and test data."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:26:36.568825Z",
"iopub.status.busy": "2024-08-20T01:26:36.568542Z",
"iopub.status.idle": "2024-08-20T01:26:37.044268Z",
"shell.execute_reply": "2024-08-20T01:26:37.043534Z"
},
"id": "YoUGfr1vuivl"
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_metrics(resampled_history)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "1PuH3A2vnwrh"
},
"source": [
"### Re-train\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "KFLxRL8eoDE5"
},
"source": [
"Because training is easier on the balanced data, the above training procedure may overfit quickly.\n",
"\n",
"So break up the epochs to give the `tf.keras.callbacks.EarlyStopping` finer control over when to stop training."
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:26:37.048305Z",
"iopub.status.busy": "2024-08-20T01:26:37.048009Z",
"iopub.status.idle": "2024-08-20T01:26:59.871108Z",
"shell.execute_reply": "2024-08-20T01:26:59.870235Z"
},
"id": "e_yn9I26qAHU"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:07\u001b[0m 4s/step - Brier score: 0.0213 - accuracy: 0.9700 - auc: 0.9739 - cross entropy: 0.0730 - fn: 383.0000 - fp: 1047.0000 - loss: 0.8409 - prc: 0.5295 - precision: 0.4108 - recall: 0.6559 - tn: 45457.0000 - tp: 730.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 6/20\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 13ms/step - Brier score: 0.0450 - accuracy: 0.9316 - auc: 0.9566 - cross entropy: 0.1407 - fn: 1250.6666 - fp: 2443.8333 - loss: 0.8193 - prc: 0.6030 - precision: 0.4784 - recall: 0.6540 - tn: 46663.0000 - tp: 2379.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 9/20\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0559 - accuracy: 0.9140 - auc: 0.9485 - cross entropy: 0.1713 - fn: 1718.6666 - fp: 3251.6667 - loss: 0.8042 - prc: 0.6257 - precision: 0.4960 - recall: 0.6609 - tn: 47411.7773 - tp: 3426.8889"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m12/20\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0650 - accuracy: 0.8990 - auc: 0.9414 - cross entropy: 0.1970 - fn: 2153.1667 - fp: 4058.7500 - loss: 0.7912 - prc: 0.6431 - precision: 0.5080 - recall: 0.6684 - tn: 48164.5000 - tp: 4504.5835"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m15/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0729 - accuracy: 0.8862 - auc: 0.9353 - cross entropy: 0.2192 - fn: 2565.8000 - fp: 4859.3999 - loss: 0.7802 - prc: 0.6572 - precision: 0.5174 - recall: 0.6756 - tn: 48912.2656 - tp: 5615.5332"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m18/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0797 - accuracy: 0.8751 - auc: 0.9299 - cross entropy: 0.2383 - fn: 2957.5000 - fp: 5649.2222 - loss: 0.7703 - prc: 0.6693 - precision: 0.5252 - recall: 0.6824 - tn: 49668.6094 - tp: 6749.6665"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 146ms/step - Brier score: 0.0854 - accuracy: 0.8656 - auc: 0.9253 - cross entropy: 0.2545 - fn: 3317.8572 - fp: 6401.5239 - loss: 0.7612 - prc: 0.6796 - precision: 0.5317 - recall: 0.6887 - tn: 50418.2383 - tp: 7861.8569 - val_Brier score: 0.2768 - val_accuracy: 0.4990 - val_auc: 0.9432 - val_cross entropy: 0.7582 - val_fn: 3.0000 - val_fp: 22829.0000 - val_loss: 0.7582 - val_prc: 0.3111 - val_precision: 0.0034 - val_recall: 0.9634 - val_tn: 22658.0000 - val_tp: 79.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.2100 - accuracy: 0.6558 - auc: 0.7746 - cross entropy: 0.6032 - fn: 215.0000 - fp: 490.0000 - loss: 0.6032 - prc: 0.8306 - precision: 0.6313 - recall: 0.7960 - tn: 504.0000 - tp: 839.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.2066 - accuracy: 0.6657 - auc: 0.7846 - cross entropy: 0.5973 - fn: 589.4000 - fp: 1448.8000 - loss: 0.5973 - prc: 0.8339 - precision: 0.6354 - recall: 0.8086 - tn: 1563.8000 - tp: 2542.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.2049 - accuracy: 0.6694 - auc: 0.7891 - cross entropy: 0.5925 - fn: 862.6250 - fp: 2153.6250 - loss: 0.5925 - prc: 0.8372 - precision: 0.6378 - recall: 0.8125 - tn: 2373.6250 - tp: 3826.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.2036 - accuracy: 0.6721 - auc: 0.7931 - cross entropy: 0.5885 - fn: 1123.2727 - fp: 2861.4546 - loss: 0.5885 - prc: 0.8401 - precision: 0.6390 - recall: 0.8156 - tn: 3195.9092 - tp: 5107.3638"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.2023 - accuracy: 0.6745 - auc: 0.7966 - cross entropy: 0.5846 - fn: 1374.2142 - fp: 3562.7144 - loss: 0.5846 - prc: 0.8428 - precision: 0.6402 - recall: 0.8185 - tn: 4027.2144 - tp: 6395.8569"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.2011 - accuracy: 0.6765 - auc: 0.7998 - cross entropy: 0.5811 - fn: 1617.7059 - fp: 4266.0000 - loss: 0.5811 - prc: 0.8453 - precision: 0.6411 - recall: 0.8210 - tn: 4858.1763 - tp: 7690.1177"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.2001 - accuracy: 0.6783 - auc: 0.8027 - cross entropy: 0.5781 - fn: 1853.7000 - fp: 4965.5000 - loss: 0.5781 - prc: 0.8474 - precision: 0.6418 - recall: 0.8233 - tn: 5702.1001 - tp: 8982.7002"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 28ms/step - Brier score: 0.1998 - accuracy: 0.6788 - auc: 0.8035 - cross entropy: 0.5771 - fn: 1924.4762 - fp: 5174.4287 - loss: 0.5771 - prc: 0.8480 - precision: 0.6421 - recall: 0.8240 - tn: 5957.5239 - tp: 9374.0479 - val_Brier score: 0.2384 - val_accuracy: 0.6159 - val_auc: 0.9514 - val_cross entropy: 0.6743 - val_fn: 3.0000 - val_fp: 17501.0000 - val_loss: 0.6743 - val_prc: 0.6435 - val_precision: 0.0045 - val_recall: 0.9634 - val_tn: 27986.0000 - val_tp: 79.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.1877 - accuracy: 0.7012 - auc: 0.8394 - cross entropy: 0.5449 - fn: 148.0000 - fp: 464.0000 - loss: 0.5449 - prc: 0.8757 - precision: 0.6530 - recall: 0.8550 - tn: 563.0000 - tp: 873.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1819 - accuracy: 0.7117 - auc: 0.8470 - cross entropy: 0.5315 - fn: 443.4000 - fp: 1310.0000 - loss: 0.5315 - prc: 0.8797 - precision: 0.6638 - recall: 0.8545 - tn: 1774.8000 - tp: 2615.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1802 - accuracy: 0.7155 - auc: 0.8500 - cross entropy: 0.5266 - fn: 654.5000 - fp: 1937.1250 - loss: 0.5266 - prc: 0.8817 - precision: 0.6669 - recall: 0.8561 - tn: 2695.3750 - tp: 3929.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.1790 - accuracy: 0.7180 - auc: 0.8519 - cross entropy: 0.5232 - fn: 866.6364 - fp: 2555.0000 - loss: 0.5232 - prc: 0.8831 - precision: 0.6692 - recall: 0.8569 - tn: 3627.3635 - tp: 5239.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.1780 - accuracy: 0.7200 - auc: 0.8535 - cross entropy: 0.5202 - fn: 1082.5714 - fp: 3161.0000 - loss: 0.5202 - prc: 0.8844 - precision: 0.6711 - recall: 0.8572 - tn: 4565.6431 - tp: 6550.7856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.1771 - accuracy: 0.7218 - auc: 0.8548 - cross entropy: 0.5176 - fn: 1298.4117 - fp: 3757.9412 - loss: 0.5176 - prc: 0.8855 - precision: 0.6729 - recall: 0.8574 - tn: 5510.4707 - tp: 7865.1763"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.1762 - accuracy: 0.7235 - auc: 0.8561 - cross entropy: 0.5150 - fn: 1511.8000 - fp: 4341.1499 - loss: 0.5150 - prc: 0.8867 - precision: 0.6749 - recall: 0.8578 - tn: 6462.7500 - tp: 9188.2998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 28ms/step - Brier score: 0.1759 - accuracy: 0.7240 - auc: 0.8564 - cross entropy: 0.5143 - fn: 1575.7620 - fp: 4516.0952 - loss: 0.5143 - prc: 0.8870 - precision: 0.6754 - recall: 0.8579 - tn: 6751.8569 - tp: 9586.7617 - val_Brier score: 0.2005 - val_accuracy: 0.7314 - val_auc: 0.9561 - val_cross entropy: 0.5917 - val_fn: 4.0000 - val_fp: 12234.0000 - val_loss: 0.5917 - val_prc: 0.7039 - val_precision: 0.0063 - val_recall: 0.9512 - val_tn: 33253.0000 - val_tp: 78.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.1585 - accuracy: 0.7573 - auc: 0.8847 - cross entropy: 0.4748 - fn: 129.0000 - fp: 368.0000 - loss: 0.4748 - prc: 0.9040 - precision: 0.7068 - recall: 0.8730 - tn: 664.0000 - tp: 887.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1549 - accuracy: 0.7641 - auc: 0.8862 - cross entropy: 0.4613 - fn: 404.0000 - fp: 1038.2000 - loss: 0.4613 - prc: 0.9102 - precision: 0.7197 - recall: 0.8709 - tn: 2002.8000 - tp: 2699.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1546 - accuracy: 0.7642 - auc: 0.8857 - cross entropy: 0.4598 - fn: 616.8750 - fp: 1551.0000 - loss: 0.4598 - prc: 0.9107 - precision: 0.7206 - recall: 0.8688 - tn: 3019.6250 - tp: 4028.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.1545 - accuracy: 0.7638 - auc: 0.8854 - cross entropy: 0.4590 - fn: 833.0909 - fp: 2068.9092 - loss: 0.4590 - prc: 0.9108 - precision: 0.7203 - recall: 0.8672 - tn: 4038.9092 - tp: 5347.0908"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.1541 - accuracy: 0.7643 - auc: 0.8857 - cross entropy: 0.4577 - fn: 1044.7142 - fp: 2569.4285 - loss: 0.4577 - prc: 0.9113 - precision: 0.7210 - recall: 0.8664 - tn: 5074.6431 - tp: 6671.2144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.1536 - accuracy: 0.7653 - auc: 0.8863 - cross entropy: 0.4560 - fn: 1251.2941 - fp: 3056.1177 - loss: 0.4560 - prc: 0.9119 - precision: 0.7222 - recall: 0.8662 - tn: 6119.6470 - tp: 8004.9414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.1530 - accuracy: 0.7663 - auc: 0.8870 - cross entropy: 0.4542 - fn: 1454.6000 - fp: 3535.7000 - loss: 0.4542 - prc: 0.9126 - precision: 0.7232 - recall: 0.8662 - tn: 7182.1001 - tp: 9331.5996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 28ms/step - Brier score: 0.1528 - accuracy: 0.7666 - auc: 0.8872 - cross entropy: 0.4537 - fn: 1515.7620 - fp: 3679.7620 - loss: 0.4537 - prc: 0.9127 - precision: 0.7236 - recall: 0.8662 - tn: 7503.4761 - tp: 9731.4766 - val_Brier score: 0.1704 - val_accuracy: 0.8147 - val_auc: 0.9601 - val_cross entropy: 0.5256 - val_fn: 5.0000 - val_fp: 8439.0000 - val_loss: 0.5256 - val_prc: 0.7351 - val_precision: 0.0090 - val_recall: 0.9390 - val_tn: 37048.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 5/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.1449 - accuracy: 0.7793 - auc: 0.8947 - cross entropy: 0.4280 - fn: 145.0000 - fp: 307.0000 - loss: 0.4280 - prc: 0.9209 - precision: 0.7418 - recall: 0.8588 - tn: 714.0000 - tp: 882.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.1442 - accuracy: 0.7810 - auc: 0.8945 - cross entropy: 0.4267 - fn: 368.7500 - fp: 749.7500 - loss: 0.4267 - prc: 0.9218 - precision: 0.7474 - recall: 0.8580 - tn: 1769.7500 - tp: 2231.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1428 - accuracy: 0.7839 - auc: 0.8965 - cross entropy: 0.4239 - fn: 578.5714 - fp: 1176.4286 - loss: 0.4239 - prc: 0.9235 - precision: 0.7512 - recall: 0.8602 - tn: 2838.8572 - tp: 3598.1428"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1420 - accuracy: 0.7863 - auc: 0.8978 - cross entropy: 0.4221 - fn: 781.5000 - fp: 1598.5000 - loss: 0.4221 - prc: 0.9244 - precision: 0.7533 - recall: 0.8619 - tn: 3936.5000 - tp: 4947.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1415 - accuracy: 0.7878 - auc: 0.8986 - cross entropy: 0.4211 - fn: 983.0000 - fp: 2021.3846 - loss: 0.4211 - prc: 0.9248 - precision: 0.7543 - recall: 0.8629 - tn: 5049.5386 - tp: 6282.0771"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1409 - accuracy: 0.7895 - auc: 0.8997 - cross entropy: 0.4196 - fn: 1181.5625 - fp: 2430.9375 - loss: 0.4196 - prc: 0.9254 - precision: 0.7555 - recall: 0.8638 - tn: 6180.5625 - tp: 7614.9375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.1403 - accuracy: 0.7908 - auc: 0.9006 - cross entropy: 0.4182 - fn: 1380.8422 - fp: 2837.9473 - loss: 0.4182 - prc: 0.9259 - precision: 0.7566 - recall: 0.8644 - tn: 7315.1055 - tp: 8946.1055"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 26ms/step - Brier score: 0.1399 - accuracy: 0.7916 - auc: 0.9011 - cross entropy: 0.4172 - fn: 1509.0476 - fp: 3090.4285 - loss: 0.4172 - prc: 0.9263 - precision: 0.7574 - recall: 0.8647 - tn: 8035.0000 - tp: 9796.0000 - val_Brier score: 0.1466 - val_accuracy: 0.8680 - val_auc: 0.9637 - val_cross entropy: 0.4722 - val_fn: 5.0000 - val_fp: 6008.0000 - val_loss: 0.4722 - val_prc: 0.7597 - val_precision: 0.0127 - val_recall: 0.9390 - val_tn: 39479.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.1279 - accuracy: 0.8120 - auc: 0.9153 - cross entropy: 0.3878 - fn: 128.0000 - fp: 257.0000 - loss: 0.3878 - prc: 0.9376 - precision: 0.7818 - recall: 0.8780 - tn: 742.0000 - tp: 921.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.1300 - accuracy: 0.8089 - auc: 0.9128 - cross entropy: 0.3926 - fn: 391.2000 - fp: 785.8000 - loss: 0.3926 - prc: 0.9362 - precision: 0.7777 - recall: 0.8760 - tn: 2219.6001 - tp: 2747.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.1299 - accuracy: 0.8099 - auc: 0.9128 - cross entropy: 0.3924 - fn: 583.7500 - fp: 1164.6250 - loss: 0.3924 - prc: 0.9365 - precision: 0.7793 - recall: 0.8764 - tn: 3331.5000 - tp: 4136.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1295 - accuracy: 0.8108 - auc: 0.9130 - cross entropy: 0.3914 - fn: 781.5455 - fp: 1533.0000 - loss: 0.3914 - prc: 0.9367 - precision: 0.7808 - recall: 0.8760 - tn: 4465.6362 - tp: 5507.8184"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1292 - accuracy: 0.8116 - auc: 0.9134 - cross entropy: 0.3906 - fn: 974.6429 - fp: 1902.0000 - loss: 0.3906 - prc: 0.9369 - precision: 0.7816 - recall: 0.8760 - tn: 5612.8569 - tp: 6870.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1288 - accuracy: 0.8125 - auc: 0.9138 - cross entropy: 0.3896 - fn: 1168.1177 - fp: 2259.7646 - loss: 0.3896 - prc: 0.9372 - precision: 0.7826 - recall: 0.8759 - tn: 6781.1763 - tp: 8222.9414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.1284 - accuracy: 0.8134 - auc: 0.9143 - cross entropy: 0.3886 - fn: 1361.3500 - fp: 2613.5500 - loss: 0.3886 - prc: 0.9374 - precision: 0.7834 - recall: 0.8757 - tn: 7960.5498 - tp: 9568.5498"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.1283 - accuracy: 0.8136 - auc: 0.9144 - cross entropy: 0.3884 - fn: 1419.9048 - fp: 2720.1904 - loss: 0.3884 - prc: 0.9374 - precision: 0.7837 - recall: 0.8757 - tn: 8316.5713 - tp: 9973.8096 - val_Brier score: 0.1263 - val_accuracy: 0.9040 - val_auc: 0.9668 - val_cross entropy: 0.4258 - val_fn: 5.0000 - val_fp: 4368.0000 - val_loss: 0.4258 - val_prc: 0.7771 - val_precision: 0.0173 - val_recall: 0.9390 - val_tn: 41119.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.1175 - accuracy: 0.8320 - auc: 0.9264 - cross entropy: 0.3617 - fn: 128.0000 - fp: 216.0000 - loss: 0.3617 - prc: 0.9441 - precision: 0.8056 - recall: 0.8749 - tn: 809.0000 - tp: 895.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.1179 - accuracy: 0.8327 - auc: 0.9269 - cross entropy: 0.3619 - fn: 379.4000 - fp: 648.4000 - loss: 0.3619 - prc: 0.9446 - precision: 0.8046 - recall: 0.8756 - tn: 2448.8000 - tp: 2667.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.1178 - accuracy: 0.8328 - auc: 0.9270 - cross entropy: 0.3612 - fn: 572.5000 - fp: 967.3750 - loss: 0.3612 - prc: 0.9449 - precision: 0.8053 - recall: 0.8753 - tn: 3664.1250 - tp: 4012.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1174 - accuracy: 0.8334 - auc: 0.9272 - cross entropy: 0.3602 - fn: 766.4545 - fp: 1275.3636 - loss: 0.3602 - prc: 0.9452 - precision: 0.8066 - recall: 0.8752 - tn: 4885.0908 - tp: 5361.0908"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1171 - accuracy: 0.8341 - auc: 0.9274 - cross entropy: 0.3594 - fn: 959.0000 - fp: 1575.9286 - loss: 0.3594 - prc: 0.9455 - precision: 0.8081 - recall: 0.8752 - tn: 6110.2144 - tp: 6714.8569"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1168 - accuracy: 0.8346 - auc: 0.9276 - cross entropy: 0.3585 - fn: 1154.1177 - fp: 1875.5294 - loss: 0.3585 - prc: 0.9458 - precision: 0.8093 - recall: 0.8751 - tn: 7327.8237 - tp: 8074.5293"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1165 - accuracy: 0.8350 - auc: 0.9277 - cross entropy: 0.3577 - fn: 1351.0000 - fp: 2173.8999 - loss: 0.3577 - prc: 0.9460 - precision: 0.8102 - recall: 0.8749 - tn: 8551.4502 - tp: 9427.6504"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.1164 - accuracy: 0.8351 - auc: 0.9278 - cross entropy: 0.3575 - fn: 1410.5238 - fp: 2263.9524 - loss: 0.3575 - prc: 0.9460 - precision: 0.8105 - recall: 0.8749 - tn: 8921.5713 - tp: 9834.4287 - val_Brier score: 0.1079 - val_accuracy: 0.9311 - val_auc: 0.9695 - val_cross entropy: 0.3819 - val_fn: 5.0000 - val_fp: 3136.0000 - val_loss: 0.3819 - val_prc: 0.7823 - val_precision: 0.0240 - val_recall: 0.9390 - val_tn: 42351.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 8/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.1090 - accuracy: 0.8384 - auc: 0.9367 - cross entropy: 0.3375 - fn: 123.0000 - fp: 208.0000 - loss: 0.3375 - prc: 0.9503 - precision: 0.8092 - recall: 0.8776 - tn: 835.0000 - tp: 882.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.1099 - accuracy: 0.8407 - auc: 0.9340 - cross entropy: 0.3399 - fn: 383.4000 - fp: 590.8000 - loss: 0.3399 - prc: 0.9497 - precision: 0.8168 - recall: 0.8748 - tn: 2503.0000 - tp: 2666.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.1097 - accuracy: 0.8421 - auc: 0.9337 - cross entropy: 0.3394 - fn: 578.5000 - fp: 865.7500 - loss: 0.3394 - prc: 0.9497 - precision: 0.8196 - recall: 0.8742 - tn: 3772.7500 - tp: 3999.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.1093 - accuracy: 0.8435 - auc: 0.9338 - cross entropy: 0.3385 - fn: 772.1818 - fp: 1132.1818 - loss: 0.3385 - prc: 0.9499 - precision: 0.8220 - recall: 0.8740 - tn: 5049.0908 - tp: 5334.5454"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1089 - accuracy: 0.8448 - auc: 0.9340 - cross entropy: 0.3374 - fn: 966.0000 - fp: 1386.9286 - loss: 0.3374 - prc: 0.9502 - precision: 0.8245 - recall: 0.8740 - tn: 6318.5713 - tp: 6688.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1085 - accuracy: 0.8459 - auc: 0.9342 - cross entropy: 0.3364 - fn: 1159.8823 - fp: 1639.1765 - loss: 0.3364 - prc: 0.9505 - precision: 0.8265 - recall: 0.8741 - tn: 7594.7646 - tp: 8038.1763"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1082 - accuracy: 0.8468 - auc: 0.9344 - cross entropy: 0.3356 - fn: 1355.0500 - fp: 1889.1500 - loss: 0.3356 - prc: 0.9508 - precision: 0.8281 - recall: 0.8740 - tn: 8875.1504 - tp: 9384.6504"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.1081 - accuracy: 0.8470 - auc: 0.9345 - cross entropy: 0.3353 - fn: 1414.0952 - fp: 1964.7620 - loss: 0.3353 - prc: 0.9508 - precision: 0.8286 - recall: 0.8740 - tn: 9261.8096 - tp: 9789.8096 - val_Brier score: 0.0926 - val_accuracy: 0.9487 - val_auc: 0.9721 - val_cross entropy: 0.3441 - val_fn: 5.0000 - val_fp: 2334.0000 - val_loss: 0.3441 - val_prc: 0.7887 - val_precision: 0.0319 - val_recall: 0.9390 - val_tn: 43153.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0989 - accuracy: 0.8643 - auc: 0.9432 - cross entropy: 0.3096 - fn: 131.0000 - fp: 147.0000 - loss: 0.3096 - prc: 0.9580 - precision: 0.8599 - recall: 0.8732 - tn: 868.0000 - tp: 902.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.1001 - accuracy: 0.8652 - auc: 0.9413 - cross entropy: 0.3144 - fn: 385.8000 - fp: 438.8000 - loss: 0.3144 - prc: 0.9566 - precision: 0.8605 - recall: 0.8751 - tn: 2602.0000 - tp: 2717.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.1003 - accuracy: 0.8654 - auc: 0.9411 - cross entropy: 0.3153 - fn: 577.0000 - fp: 661.0000 - loss: 0.3153 - prc: 0.9561 - precision: 0.8602 - recall: 0.8754 - tn: 3909.5000 - tp: 4068.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.1002 - accuracy: 0.8656 - auc: 0.9412 - cross entropy: 0.3152 - fn: 761.4545 - fp: 885.5455 - loss: 0.3152 - prc: 0.9560 - precision: 0.8599 - recall: 0.8762 - tn: 5213.0000 - tp: 5428.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.1000 - accuracy: 0.8660 - auc: 0.9415 - cross entropy: 0.3147 - fn: 944.8571 - fp: 1107.2858 - loss: 0.3147 - prc: 0.9562 - precision: 0.8599 - recall: 0.8769 - tn: 6517.4287 - tp: 6790.4287"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0998 - accuracy: 0.8662 - auc: 0.9417 - cross entropy: 0.3142 - fn: 1134.8823 - fp: 1323.8823 - loss: 0.3142 - prc: 0.9563 - precision: 0.8601 - recall: 0.8770 - tn: 7826.5884 - tp: 8146.6470"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0995 - accuracy: 0.8665 - auc: 0.9418 - cross entropy: 0.3136 - fn: 1327.3000 - fp: 1532.2500 - loss: 0.3136 - prc: 0.9564 - precision: 0.8606 - recall: 0.8769 - tn: 9146.5498 - tp: 9497.9004"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0994 - accuracy: 0.8665 - auc: 0.9419 - cross entropy: 0.3134 - fn: 1385.7142 - fp: 1594.3810 - loss: 0.3134 - prc: 0.9564 - precision: 0.8608 - recall: 0.8769 - tn: 9544.9521 - tp: 9905.4287 - val_Brier score: 0.0800 - val_accuracy: 0.9605 - val_auc: 0.9745 - val_cross entropy: 0.3111 - val_fn: 5.0000 - val_fp: 1794.0000 - val_loss: 0.3111 - val_prc: 0.7932 - val_precision: 0.0412 - val_recall: 0.9390 - val_tn: 43693.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 10/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0966 - accuracy: 0.8667 - auc: 0.9446 - cross entropy: 0.3052 - fn: 126.0000 - fp: 147.0000 - loss: 0.3052 - prc: 0.9559 - precision: 0.8574 - recall: 0.8752 - tn: 891.0000 - tp: 884.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0952 - accuracy: 0.8692 - auc: 0.9462 - cross entropy: 0.3010 - fn: 379.0000 - fp: 418.8000 - loss: 0.3010 - prc: 0.9585 - precision: 0.8642 - recall: 0.8768 - tn: 2628.8000 - tp: 2717.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0946 - accuracy: 0.8705 - auc: 0.9466 - cross entropy: 0.2997 - fn: 566.7500 - fp: 616.0000 - loss: 0.2997 - prc: 0.9592 - precision: 0.8667 - recall: 0.8775 - tn: 3944.2500 - tp: 4089.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0943 - accuracy: 0.8716 - auc: 0.9468 - cross entropy: 0.2988 - fn: 754.7273 - fp: 805.9091 - loss: 0.2988 - prc: 0.9595 - precision: 0.8686 - recall: 0.8777 - tn: 5281.3638 - tp: 5446.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0939 - accuracy: 0.8727 - auc: 0.9470 - cross entropy: 0.2978 - fn: 941.2143 - fp: 988.8571 - loss: 0.2978 - prc: 0.9598 - precision: 0.8702 - recall: 0.8779 - tn: 6635.7144 - tp: 6794.2144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0936 - accuracy: 0.8735 - auc: 0.9472 - cross entropy: 0.2969 - fn: 1128.7059 - fp: 1171.2354 - loss: 0.2969 - prc: 0.9600 - precision: 0.8715 - recall: 0.8780 - tn: 7981.7061 - tp: 8150.3530"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0933 - accuracy: 0.8741 - auc: 0.9474 - cross entropy: 0.2963 - fn: 1315.4000 - fp: 1354.2500 - loss: 0.2963 - prc: 0.9602 - precision: 0.8724 - recall: 0.8781 - tn: 9325.2002 - tp: 9509.1504"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 23ms/step - Brier score: 0.0932 - accuracy: 0.8743 - auc: 0.9474 - cross entropy: 0.2961 - fn: 1371.6190 - fp: 1409.3810 - loss: 0.2961 - prc: 0.9602 - precision: 0.8727 - recall: 0.8781 - tn: 9730.0000 - tp: 9919.4766 - val_Brier score: 0.0703 - val_accuracy: 0.9667 - val_auc: 0.9773 - val_cross entropy: 0.2844 - val_fn: 5.0000 - val_fp: 1514.0000 - val_loss: 0.2844 - val_prc: 0.7895 - val_precision: 0.0484 - val_recall: 0.9390 - val_tn: 43973.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 11/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0910 - accuracy: 0.8760 - auc: 0.9483 - cross entropy: 0.2889 - fn: 132.0000 - fp: 122.0000 - loss: 0.2889 - prc: 0.9586 - precision: 0.8738 - recall: 0.8649 - tn: 949.0000 - tp: 845.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0892 - accuracy: 0.8800 - auc: 0.9509 - cross entropy: 0.2842 - fn: 376.4000 - fp: 353.8000 - loss: 0.2842 - prc: 0.9621 - precision: 0.8816 - recall: 0.8754 - tn: 2716.2000 - tp: 2697.6001"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0888 - accuracy: 0.8810 - auc: 0.9512 - cross entropy: 0.2832 - fn: 559.1250 - fp: 528.0000 - loss: 0.2832 - prc: 0.9628 - precision: 0.8832 - recall: 0.8773 - tn: 4057.3750 - tp: 4071.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0886 - accuracy: 0.8815 - auc: 0.9513 - cross entropy: 0.2826 - fn: 740.0000 - fp: 704.8182 - loss: 0.2826 - prc: 0.9631 - precision: 0.8838 - recall: 0.8784 - tn: 5402.5454 - tp: 5440.6362"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0883 - accuracy: 0.8821 - auc: 0.9516 - cross entropy: 0.2819 - fn: 920.5714 - fp: 875.0000 - loss: 0.2819 - prc: 0.9633 - precision: 0.8845 - recall: 0.8791 - tn: 6766.9287 - tp: 6797.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0880 - accuracy: 0.8826 - auc: 0.9518 - cross entropy: 0.2811 - fn: 1102.6471 - fp: 1040.4706 - loss: 0.2811 - prc: 0.9635 - precision: 0.8853 - recall: 0.8795 - tn: 8134.4707 - tp: 8154.4116"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0877 - accuracy: 0.8831 - auc: 0.9520 - cross entropy: 0.2806 - fn: 1286.4500 - fp: 1202.4500 - loss: 0.2806 - prc: 0.9636 - precision: 0.8860 - recall: 0.8797 - tn: 9497.4004 - tp: 9517.7002"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0877 - accuracy: 0.8832 - auc: 0.9520 - cross entropy: 0.2804 - fn: 1342.0000 - fp: 1251.1904 - loss: 0.2804 - prc: 0.9637 - precision: 0.8863 - recall: 0.8798 - tn: 9908.1904 - tp: 9929.0957 - val_Brier score: 0.0620 - val_accuracy: 0.9704 - val_auc: 0.9792 - val_cross entropy: 0.2602 - val_fn: 5.0000 - val_fp: 1345.0000 - val_loss: 0.2602 - val_prc: 0.7840 - val_precision: 0.0541 - val_recall: 0.9390 - val_tn: 44142.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 12/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0809 - accuracy: 0.8911 - auc: 0.9575 - cross entropy: 0.2598 - fn: 127.0000 - fp: 96.0000 - loss: 0.2598 - prc: 0.9681 - precision: 0.9046 - recall: 0.8775 - tn: 915.0000 - tp: 910.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0815 - accuracy: 0.8923 - auc: 0.9573 - cross entropy: 0.2623 - fn: 361.8000 - fp: 298.4000 - loss: 0.2623 - prc: 0.9672 - precision: 0.9015 - recall: 0.8811 - tn: 2776.3999 - tp: 2707.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0822 - accuracy: 0.8909 - auc: 0.9564 - cross entropy: 0.2641 - fn: 551.7500 - fp: 460.0000 - loss: 0.2641 - prc: 0.9666 - precision: 0.8997 - recall: 0.8804 - tn: 4142.6250 - tp: 4061.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0823 - accuracy: 0.8907 - auc: 0.9562 - cross entropy: 0.2646 - fn: 735.1818 - fp: 615.1818 - loss: 0.2646 - prc: 0.9664 - precision: 0.8991 - recall: 0.8804 - tn: 5522.6362 - tp: 5415.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0823 - accuracy: 0.8907 - auc: 0.9561 - cross entropy: 0.2646 - fn: 917.9286 - fp: 765.8571 - loss: 0.2646 - prc: 0.9664 - precision: 0.8992 - recall: 0.8806 - tn: 6894.9287 - tp: 6781.2856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0822 - accuracy: 0.8909 - auc: 0.9561 - cross entropy: 0.2646 - fn: 1099.0000 - fp: 913.8823 - loss: 0.2646 - prc: 0.9665 - precision: 0.8993 - recall: 0.8807 - tn: 8288.7646 - tp: 8130.3530"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0822 - accuracy: 0.8910 - auc: 0.9562 - cross entropy: 0.2645 - fn: 1280.2500 - fp: 1060.7000 - loss: 0.2645 - prc: 0.9665 - precision: 0.8994 - recall: 0.8808 - tn: 9689.2500 - tp: 9473.7998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0821 - accuracy: 0.8911 - auc: 0.9562 - cross entropy: 0.2644 - fn: 1335.1904 - fp: 1104.5238 - loss: 0.2644 - prc: 0.9665 - precision: 0.8995 - recall: 0.8808 - tn: 10111.1426 - tp: 9879.6191 - val_Brier score: 0.0550 - val_accuracy: 0.9731 - val_auc: 0.9809 - val_cross entropy: 0.2388 - val_fn: 5.0000 - val_fp: 1223.0000 - val_loss: 0.2388 - val_prc: 0.7881 - val_precision: 0.0592 - val_recall: 0.9390 - val_tn: 44264.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 13/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0786 - accuracy: 0.9004 - auc: 0.9579 - cross entropy: 0.2574 - fn: 106.0000 - fp: 98.0000 - loss: 0.2574 - prc: 0.9671 - precision: 0.9028 - recall: 0.8957 - tn: 934.0000 - tp: 910.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0803 - accuracy: 0.8953 - auc: 0.9568 - cross entropy: 0.2604 - fn: 354.6000 - fp: 291.8000 - loss: 0.2604 - prc: 0.9668 - precision: 0.9029 - recall: 0.8859 - tn: 2781.6001 - tp: 2716.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0799 - accuracy: 0.8958 - auc: 0.9574 - cross entropy: 0.2590 - fn: 529.7500 - fp: 429.2500 - loss: 0.2590 - prc: 0.9672 - precision: 0.9038 - recall: 0.8854 - tn: 4192.5000 - tp: 4064.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0795 - accuracy: 0.8963 - auc: 0.9580 - cross entropy: 0.2579 - fn: 703.6364 - fp: 564.8182 - loss: 0.2579 - prc: 0.9676 - precision: 0.9046 - recall: 0.8854 - tn: 5606.2729 - tp: 5413.2729"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0791 - accuracy: 0.8968 - auc: 0.9584 - cross entropy: 0.2572 - fn: 878.7857 - fp: 697.7143 - loss: 0.2572 - prc: 0.9677 - precision: 0.9054 - recall: 0.8853 - tn: 7019.2856 - tp: 6764.2144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0789 - accuracy: 0.8970 - auc: 0.9587 - cross entropy: 0.2566 - fn: 1055.1765 - fp: 832.6470 - loss: 0.2566 - prc: 0.9679 - precision: 0.9058 - recall: 0.8852 - tn: 8432.7646 - tp: 8111.4116"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0787 - accuracy: 0.8973 - auc: 0.9589 - cross entropy: 0.2560 - fn: 1228.5000 - fp: 967.0500 - loss: 0.2560 - prc: 0.9680 - precision: 0.9062 - recall: 0.8853 - tn: 9846.1504 - tp: 9462.2998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0786 - accuracy: 0.8973 - auc: 0.9590 - cross entropy: 0.2559 - fn: 1280.6190 - fp: 1007.5714 - loss: 0.2559 - prc: 0.9681 - precision: 0.9063 - recall: 0.8853 - tn: 10273.3809 - tp: 9868.9043 - val_Brier score: 0.0492 - val_accuracy: 0.9750 - val_auc: 0.9816 - val_cross entropy: 0.2201 - val_fn: 5.0000 - val_fp: 1134.0000 - val_loss: 0.2201 - val_prc: 0.7912 - val_precision: 0.0636 - val_recall: 0.9390 - val_tn: 44353.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 14/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0750 - accuracy: 0.9087 - auc: 0.9630 - cross entropy: 0.2465 - fn: 102.0000 - fp: 85.0000 - loss: 0.2465 - prc: 0.9716 - precision: 0.9146 - recall: 0.8992 - tn: 951.0000 - tp: 910.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0744 - accuracy: 0.9070 - auc: 0.9630 - cross entropy: 0.2442 - fn: 329.0000 - fp: 243.6000 - loss: 0.2442 - prc: 0.9715 - precision: 0.9175 - recall: 0.8939 - tn: 2828.3999 - tp: 2743.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0744 - accuracy: 0.9066 - auc: 0.9631 - cross entropy: 0.2438 - fn: 498.2500 - fp: 365.1250 - loss: 0.2438 - prc: 0.9715 - precision: 0.9179 - recall: 0.8931 - tn: 4233.5000 - tp: 4119.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0743 - accuracy: 0.9065 - auc: 0.9631 - cross entropy: 0.2434 - fn: 612.0000 - fp: 445.0000 - loss: 0.2434 - prc: 0.9716 - precision: 0.9182 - recall: 0.8926 - tn: 5171.1001 - tp: 5035.8999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0741 - accuracy: 0.9064 - auc: 0.9631 - cross entropy: 0.2430 - fn: 783.6923 - fp: 562.7692 - loss: 0.2430 - prc: 0.9716 - precision: 0.9186 - recall: 0.8920 - tn: 6586.1538 - tp: 6403.3848"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0740 - accuracy: 0.9064 - auc: 0.9632 - cross entropy: 0.2427 - fn: 952.4375 - fp: 680.4375 - loss: 0.2427 - prc: 0.9716 - precision: 0.9188 - recall: 0.8917 - tn: 8009.1250 - tp: 7766.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0739 - accuracy: 0.9064 - auc: 0.9632 - cross entropy: 0.2424 - fn: 1124.5790 - fp: 795.7368 - loss: 0.2424 - prc: 0.9717 - precision: 0.9192 - recall: 0.8914 - tn: 9419.5791 - tp: 9140.1055"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 25ms/step - Brier score: 0.0739 - accuracy: 0.9064 - auc: 0.9633 - cross entropy: 0.2422 - fn: 1233.4762 - fp: 868.5238 - loss: 0.2422 - prc: 0.9717 - precision: 0.9194 - recall: 0.8912 - tn: 10317.9043 - tp: 10010.5713 - val_Brier score: 0.0447 - val_accuracy: 0.9759 - val_auc: 0.9824 - val_cross entropy: 0.2045 - val_fn: 5.0000 - val_fp: 1091.0000 - val_loss: 0.2045 - val_prc: 0.7934 - val_precision: 0.0659 - val_recall: 0.9390 - val_tn: 44396.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 15/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0742 - accuracy: 0.9019 - auc: 0.9622 - cross entropy: 0.2417 - fn: 117.0000 - fp: 84.0000 - loss: 0.2417 - prc: 0.9700 - precision: 0.9133 - recall: 0.8832 - tn: 962.0000 - tp: 885.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0740 - accuracy: 0.9016 - auc: 0.9622 - cross entropy: 0.2411 - fn: 348.6000 - fp: 253.8000 - loss: 0.2411 - prc: 0.9704 - precision: 0.9132 - recall: 0.8846 - tn: 2850.2000 - tp: 2691.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0738 - accuracy: 0.9023 - auc: 0.9625 - cross entropy: 0.2405 - fn: 515.1250 - fp: 380.3750 - loss: 0.2405 - prc: 0.9707 - precision: 0.9137 - recall: 0.8862 - tn: 4262.8750 - tp: 4057.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0735 - accuracy: 0.9030 - auc: 0.9628 - cross entropy: 0.2400 - fn: 682.2727 - fp: 499.9091 - loss: 0.2400 - prc: 0.9710 - precision: 0.9147 - recall: 0.8870 - tn: 5685.0908 - tp: 5420.7271"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0734 - accuracy: 0.9034 - auc: 0.9629 - cross entropy: 0.2398 - fn: 855.1429 - fp: 617.2857 - loss: 0.2398 - prc: 0.9711 - precision: 0.9154 - recall: 0.8872 - tn: 7104.2856 - tp: 6783.2856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0733 - accuracy: 0.9038 - auc: 0.9631 - cross entropy: 0.2395 - fn: 1026.3529 - fp: 732.5294 - loss: 0.2395 - prc: 0.9712 - precision: 0.9162 - recall: 0.8874 - tn: 8520.1768 - tp: 8152.9414"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0731 - accuracy: 0.9041 - auc: 0.9632 - cross entropy: 0.2391 - fn: 1195.9500 - fp: 847.0000 - loss: 0.2391 - prc: 0.9713 - precision: 0.9168 - recall: 0.8876 - tn: 9944.2002 - tp: 9516.8496"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0731 - accuracy: 0.9042 - auc: 0.9633 - cross entropy: 0.2390 - fn: 1247.2380 - fp: 881.2381 - loss: 0.2390 - prc: 0.9713 - precision: 0.9170 - recall: 0.8877 - tn: 10373.6191 - tp: 9928.3809 - val_Brier score: 0.0412 - val_accuracy: 0.9767 - val_auc: 0.9828 - val_cross entropy: 0.1919 - val_fn: 5.0000 - val_fp: 1059.0000 - val_loss: 0.1919 - val_prc: 0.7955 - val_precision: 0.0678 - val_recall: 0.9390 - val_tn: 44428.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 16/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0661 - accuracy: 0.9111 - auc: 0.9710 - cross entropy: 0.2211 - fn: 107.0000 - fp: 75.0000 - loss: 0.2211 - prc: 0.9776 - precision: 0.9254 - recall: 0.8969 - tn: 935.0000 - tp: 931.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0684 - accuracy: 0.9084 - auc: 0.9680 - cross entropy: 0.2268 - fn: 329.6000 - fp: 236.8000 - loss: 0.2268 - prc: 0.9748 - precision: 0.9220 - recall: 0.8937 - tn: 2819.8000 - tp: 2757.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0692 - accuracy: 0.9077 - auc: 0.9671 - cross entropy: 0.2292 - fn: 494.5000 - fp: 362.6250 - loss: 0.2292 - prc: 0.9741 - precision: 0.9205 - recall: 0.8933 - tn: 4233.7500 - tp: 4125.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0696 - accuracy: 0.9074 - auc: 0.9667 - cross entropy: 0.2302 - fn: 661.4545 - fp: 483.8182 - loss: 0.2302 - prc: 0.9737 - precision: 0.9199 - recall: 0.8928 - tn: 5662.5454 - tp: 5480.1816"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0697 - accuracy: 0.9073 - auc: 0.9666 - cross entropy: 0.2304 - fn: 827.6429 - fp: 602.0000 - loss: 0.2304 - prc: 0.9736 - precision: 0.9199 - recall: 0.8926 - tn: 7087.2144 - tp: 6843.1431"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0698 - accuracy: 0.9075 - auc: 0.9665 - cross entropy: 0.2303 - fn: 991.5883 - fp: 716.0000 - loss: 0.2303 - prc: 0.9735 - precision: 0.9201 - recall: 0.8926 - tn: 8511.2354 - tp: 8213.1768"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0697 - accuracy: 0.9078 - auc: 0.9666 - cross entropy: 0.2301 - fn: 1155.9500 - fp: 824.3500 - loss: 0.2301 - prc: 0.9736 - precision: 0.9206 - recall: 0.8926 - tn: 9935.6504 - tp: 9588.0498"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 26ms/step - Brier score: 0.0697 - accuracy: 0.9079 - auc: 0.9666 - cross entropy: 0.2300 - fn: 1205.6666 - fp: 856.9524 - loss: 0.2300 - prc: 0.9736 - precision: 0.9208 - recall: 0.8926 - tn: 10364.8574 - tp: 10003.0000 - val_Brier score: 0.0380 - val_accuracy: 0.9775 - val_auc: 0.9833 - val_cross entropy: 0.1800 - val_fn: 5.0000 - val_fp: 1019.0000 - val_loss: 0.1800 - val_prc: 0.7976 - val_precision: 0.0703 - val_recall: 0.9390 - val_tn: 44468.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 17/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0666 - accuracy: 0.9126 - auc: 0.9702 - cross entropy: 0.2209 - fn: 99.0000 - fp: 80.0000 - loss: 0.2209 - prc: 0.9756 - precision: 0.9206 - recall: 0.9035 - tn: 942.0000 - tp: 927.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0672 - accuracy: 0.9121 - auc: 0.9692 - cross entropy: 0.2215 - fn: 324.2000 - fp: 216.0000 - loss: 0.2215 - prc: 0.9750 - precision: 0.9252 - recall: 0.8956 - tn: 2874.0000 - tp: 2729.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0672 - accuracy: 0.9125 - auc: 0.9690 - cross entropy: 0.2216 - fn: 487.7500 - fp: 316.0000 - loss: 0.2216 - prc: 0.9751 - precision: 0.9270 - recall: 0.8950 - tn: 4299.3750 - tp: 4112.8750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0673 - accuracy: 0.9125 - auc: 0.9688 - cross entropy: 0.2218 - fn: 653.3636 - fp: 421.0000 - loss: 0.2218 - prc: 0.9750 - precision: 0.9276 - recall: 0.8946 - tn: 5713.5454 - tp: 5500.0908"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0672 - accuracy: 0.9126 - auc: 0.9688 - cross entropy: 0.2215 - fn: 817.5000 - fp: 521.2857 - loss: 0.2215 - prc: 0.9752 - precision: 0.9283 - recall: 0.8946 - tn: 7127.3569 - tp: 6893.8569"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0671 - accuracy: 0.9128 - auc: 0.9688 - cross entropy: 0.2212 - fn: 981.7647 - fp: 621.1765 - loss: 0.2212 - prc: 0.9752 - precision: 0.9289 - recall: 0.8945 - tn: 8549.1768 - tp: 8279.8828"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0670 - accuracy: 0.9129 - auc: 0.9688 - cross entropy: 0.2210 - fn: 1147.2000 - fp: 718.2500 - loss: 0.2210 - prc: 0.9753 - precision: 0.9294 - recall: 0.8943 - tn: 9979.5996 - tp: 9658.9502"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 26ms/step - Brier score: 0.0670 - accuracy: 0.9130 - auc: 0.9688 - cross entropy: 0.2209 - fn: 1197.1428 - fp: 747.4286 - loss: 0.2209 - prc: 0.9753 - precision: 0.9295 - recall: 0.8943 - tn: 10411.0479 - tp: 10074.8574 - val_Brier score: 0.0358 - val_accuracy: 0.9777 - val_auc: 0.9836 - val_cross entropy: 0.1710 - val_fn: 5.0000 - val_fp: 1013.0000 - val_loss: 0.1710 - val_prc: 0.7976 - val_precision: 0.0706 - val_recall: 0.9390 - val_tn: 44474.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 18/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0675 - accuracy: 0.9116 - auc: 0.9661 - cross entropy: 0.2219 - fn: 115.0000 - fp: 66.0000 - loss: 0.2219 - prc: 0.9734 - precision: 0.9315 - recall: 0.8864 - tn: 970.0000 - tp: 897.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0669 - accuracy: 0.9122 - auc: 0.9669 - cross entropy: 0.2196 - fn: 343.4000 - fp: 194.4000 - loss: 0.2196 - prc: 0.9744 - precision: 0.9333 - recall: 0.8878 - tn: 2877.0000 - tp: 2729.2000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0666 - accuracy: 0.9127 - auc: 0.9674 - cross entropy: 0.2190 - fn: 505.6250 - fp: 295.1250 - loss: 0.2190 - prc: 0.9747 - precision: 0.9329 - recall: 0.8891 - tn: 4318.2500 - tp: 4097.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0664 - accuracy: 0.9131 - auc: 0.9678 - cross entropy: 0.2183 - fn: 665.3636 - fp: 396.0000 - loss: 0.2183 - prc: 0.9749 - precision: 0.9326 - recall: 0.8902 - tn: 5766.6362 - tp: 5460.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0662 - accuracy: 0.9134 - auc: 0.9681 - cross entropy: 0.2177 - fn: 828.6429 - fp: 493.0000 - loss: 0.2177 - prc: 0.9750 - precision: 0.9328 - recall: 0.8907 - tn: 7205.0713 - tp: 6833.2856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0659 - accuracy: 0.9137 - auc: 0.9684 - cross entropy: 0.2171 - fn: 989.4117 - fp: 589.2353 - loss: 0.2171 - prc: 0.9752 - precision: 0.9329 - recall: 0.8912 - tn: 8648.7646 - tp: 8204.5879"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0657 - accuracy: 0.9140 - auc: 0.9687 - cross entropy: 0.2165 - fn: 1147.5500 - fp: 685.8000 - loss: 0.2165 - prc: 0.9754 - precision: 0.9330 - recall: 0.8917 - tn: 10089.6504 - tp: 9581.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 26ms/step - Brier score: 0.0657 - accuracy: 0.9141 - auc: 0.9687 - cross entropy: 0.2163 - fn: 1195.1904 - fp: 714.6190 - loss: 0.2163 - prc: 0.9755 - precision: 0.9331 - recall: 0.8919 - tn: 10524.4766 - tp: 9996.1904 - val_Brier score: 0.0340 - val_accuracy: 0.9775 - val_auc: 0.9838 - val_cross entropy: 0.1632 - val_fn: 5.0000 - val_fp: 1022.0000 - val_loss: 0.1632 - val_prc: 0.7981 - val_precision: 0.0701 - val_recall: 0.9390 - val_tn: 44465.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 19/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0614 - accuracy: 0.9185 - auc: 0.9727 - cross entropy: 0.2049 - fn: 109.0000 - fp: 58.0000 - loss: 0.2049 - prc: 0.9780 - precision: 0.9395 - recall: 0.8920 - tn: 981.0000 - tp: 900.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0618 - accuracy: 0.9185 - auc: 0.9723 - cross entropy: 0.2054 - fn: 267.5000 - fp: 150.5000 - loss: 0.2054 - prc: 0.9780 - precision: 0.9382 - recall: 0.8944 - tn: 2424.7500 - tp: 2277.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0621 - accuracy: 0.9181 - auc: 0.9722 - cross entropy: 0.2063 - fn: 426.5714 - fp: 246.1429 - loss: 0.2063 - prc: 0.9781 - precision: 0.9375 - recall: 0.8952 - tn: 3853.7144 - tp: 3665.5715"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0622 - accuracy: 0.9181 - auc: 0.9721 - cross entropy: 0.2066 - fn: 585.9000 - fp: 338.2000 - loss: 0.2066 - prc: 0.9780 - precision: 0.9373 - recall: 0.8953 - tn: 5312.3999 - tp: 5027.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0623 - accuracy: 0.9181 - auc: 0.9721 - cross entropy: 0.2066 - fn: 741.9231 - fp: 432.1538 - loss: 0.2066 - prc: 0.9779 - precision: 0.9370 - recall: 0.8955 - tn: 6775.1538 - tp: 6386.7690"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0623 - accuracy: 0.9182 - auc: 0.9721 - cross entropy: 0.2066 - fn: 897.7500 - fp: 525.7500 - loss: 0.2066 - prc: 0.9779 - precision: 0.9368 - recall: 0.8957 - tn: 8237.6875 - tp: 7746.8125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0623 - accuracy: 0.9183 - auc: 0.9721 - cross entropy: 0.2066 - fn: 1053.6316 - fp: 616.4737 - loss: 0.2066 - prc: 0.9779 - precision: 0.9369 - recall: 0.8959 - tn: 9696.1055 - tp: 9113.7891"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 27ms/step - Brier score: 0.0623 - accuracy: 0.9184 - auc: 0.9721 - cross entropy: 0.2066 - fn: 1152.6190 - fp: 673.1905 - loss: 0.2066 - prc: 0.9779 - precision: 0.9370 - recall: 0.8960 - tn: 10617.4287 - tp: 9987.2383 - val_Brier score: 0.0321 - val_accuracy: 0.9777 - val_auc: 0.9842 - val_cross entropy: 0.1556 - val_fn: 5.0000 - val_fp: 1011.0000 - val_loss: 0.1556 - val_prc: 0.7999 - val_precision: 0.0708 - val_recall: 0.9390 - val_tn: 44476.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 20/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0614 - accuracy: 0.9219 - auc: 0.9724 - cross entropy: 0.2077 - fn: 103.0000 - fp: 57.0000 - loss: 0.2077 - prc: 0.9759 - precision: 0.9408 - recall: 0.8979 - tn: 982.0000 - tp: 906.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0624 - accuracy: 0.9185 - auc: 0.9720 - cross entropy: 0.2101 - fn: 270.0000 - fp: 150.2500 - loss: 0.2101 - prc: 0.9767 - precision: 0.9391 - recall: 0.8955 - tn: 2391.7500 - tp: 2308.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0623 - accuracy: 0.9181 - auc: 0.9722 - cross entropy: 0.2091 - fn: 425.5714 - fp: 249.8571 - loss: 0.2091 - prc: 0.9770 - precision: 0.9373 - recall: 0.8960 - tn: 3847.0000 - tp: 3669.5715"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0622 - accuracy: 0.9178 - auc: 0.9724 - cross entropy: 0.2085 - fn: 580.1000 - fp: 351.4000 - loss: 0.2085 - prc: 0.9772 - precision: 0.9361 - recall: 0.8964 - tn: 5298.7002 - tp: 5033.7998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0621 - accuracy: 0.9179 - auc: 0.9726 - cross entropy: 0.2078 - fn: 733.0769 - fp: 446.5385 - loss: 0.2078 - prc: 0.9773 - precision: 0.9358 - recall: 0.8968 - tn: 6755.7690 - tp: 6400.6152"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0620 - accuracy: 0.9182 - auc: 0.9727 - cross entropy: 0.2072 - fn: 885.5625 - fp: 537.1875 - loss: 0.2072 - prc: 0.9775 - precision: 0.9359 - recall: 0.8971 - tn: 8215.4375 - tp: 7769.8125"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0619 - accuracy: 0.9183 - auc: 0.9728 - cross entropy: 0.2068 - fn: 1040.4736 - fp: 627.4211 - loss: 0.2068 - prc: 0.9776 - precision: 0.9361 - recall: 0.8973 - tn: 9664.7373 - tp: 9147.3682"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 26ms/step - Brier score: 0.0618 - accuracy: 0.9184 - auc: 0.9728 - cross entropy: 0.2065 - fn: 1139.0952 - fp: 684.5238 - loss: 0.2065 - prc: 0.9777 - precision: 0.9362 - recall: 0.8974 - tn: 10583.5234 - tp: 10023.3330 - val_Brier score: 0.0304 - val_accuracy: 0.9782 - val_auc: 0.9845 - val_cross entropy: 0.1483 - val_fn: 5.0000 - val_fp: 990.0000 - val_loss: 0.1483 - val_prc: 0.8002 - val_precision: 0.0722 - val_recall: 0.9390 - val_tn: 44497.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 21/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0597 - accuracy: 0.9258 - auc: 0.9742 - cross entropy: 0.2032 - fn: 99.0000 - fp: 53.0000 - loss: 0.2032 - prc: 0.9780 - precision: 0.9446 - recall: 0.9012 - tn: 993.0000 - tp: 903.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0594 - accuracy: 0.9235 - auc: 0.9747 - cross entropy: 0.1995 - fn: 248.7500 - fp: 143.0000 - loss: 0.1995 - prc: 0.9789 - precision: 0.9411 - recall: 0.9007 - tn: 2457.5000 - tp: 2270.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0592 - accuracy: 0.9233 - auc: 0.9749 - cross entropy: 0.1987 - fn: 395.1429 - fp: 233.1429 - loss: 0.1987 - prc: 0.9791 - precision: 0.9403 - recall: 0.9013 - tn: 3933.1428 - tp: 3630.5715"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0591 - accuracy: 0.9233 - auc: 0.9750 - cross entropy: 0.1981 - fn: 542.4000 - fp: 321.5000 - loss: 0.1981 - prc: 0.9792 - precision: 0.9400 - recall: 0.9016 - tn: 5399.5000 - tp: 5000.6001"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0591 - accuracy: 0.9231 - auc: 0.9750 - cross entropy: 0.1980 - fn: 692.3846 - fp: 411.5385 - loss: 0.1980 - prc: 0.9792 - precision: 0.9397 - recall: 0.9016 - tn: 6869.7690 - tp: 6362.3076"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0592 - accuracy: 0.9231 - auc: 0.9750 - cross entropy: 0.1980 - fn: 842.5625 - fp: 497.7500 - loss: 0.1980 - prc: 0.9792 - precision: 0.9398 - recall: 0.9015 - tn: 8341.0000 - tp: 7726.6875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0592 - accuracy: 0.9231 - auc: 0.9749 - cross entropy: 0.1981 - fn: 993.4737 - fp: 584.5789 - loss: 0.1981 - prc: 0.9791 - precision: 0.9398 - recall: 0.9014 - tn: 9812.3154 - tp: 9089.6318"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 27ms/step - Brier score: 0.0593 - accuracy: 0.9230 - auc: 0.9749 - cross entropy: 0.1981 - fn: 1089.2380 - fp: 639.9524 - loss: 0.1981 - prc: 0.9791 - precision: 0.9398 - recall: 0.9014 - tn: 10744.6670 - tp: 9956.6191 - val_Brier score: 0.0289 - val_accuracy: 0.9789 - val_auc: 0.9849 - val_cross entropy: 0.1419 - val_fn: 5.0000 - val_fp: 958.0000 - val_loss: 0.1419 - val_prc: 0.8002 - val_precision: 0.0744 - val_recall: 0.9390 - val_tn: 44529.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 22/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0580 - accuracy: 0.9229 - auc: 0.9768 - cross entropy: 0.1964 - fn: 92.0000 - fp: 66.0000 - loss: 0.1964 - prc: 0.9808 - precision: 0.9352 - recall: 0.9120 - tn: 937.0000 - tp: 953.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0595 - accuracy: 0.9212 - auc: 0.9752 - cross entropy: 0.2003 - fn: 290.8000 - fp: 193.6000 - loss: 0.2003 - prc: 0.9794 - precision: 0.9347 - recall: 0.9071 - tn: 2866.6001 - tp: 2793.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0593 - accuracy: 0.9225 - auc: 0.9750 - cross entropy: 0.2003 - fn: 432.3750 - fp: 276.0000 - loss: 0.2003 - prc: 0.9792 - precision: 0.9366 - recall: 0.9068 - tn: 4336.2500 - tp: 4171.3750"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0592 - accuracy: 0.9230 - auc: 0.9750 - cross entropy: 0.2000 - fn: 576.2727 - fp: 361.2727 - loss: 0.2000 - prc: 0.9792 - precision: 0.9376 - recall: 0.9065 - tn: 5801.0000 - tp: 5549.4546"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0592 - accuracy: 0.9233 - auc: 0.9750 - cross entropy: 0.1996 - fn: 721.0714 - fp: 446.5000 - loss: 0.1996 - prc: 0.9792 - precision: 0.9381 - recall: 0.9062 - tn: 7272.5000 - tp: 6919.9287"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0591 - accuracy: 0.9236 - auc: 0.9750 - cross entropy: 0.1991 - fn: 865.6470 - fp: 528.8823 - loss: 0.1991 - prc: 0.9792 - precision: 0.9387 - recall: 0.9060 - tn: 8743.7061 - tp: 8293.7646"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0589 - accuracy: 0.9239 - auc: 0.9751 - cross entropy: 0.1985 - fn: 1010.3500 - fp: 608.5000 - loss: 0.1985 - prc: 0.9793 - precision: 0.9393 - recall: 0.9059 - tn: 10213.4004 - tp: 9671.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 26ms/step - Brier score: 0.0589 - accuracy: 0.9240 - auc: 0.9752 - cross entropy: 0.1983 - fn: 1054.1904 - fp: 632.2857 - loss: 0.1983 - prc: 0.9794 - precision: 0.9395 - recall: 0.9059 - tn: 10657.0000 - tp: 10087.0000 - val_Brier score: 0.0276 - val_accuracy: 0.9795 - val_auc: 0.9855 - val_cross entropy: 0.1360 - val_fn: 5.0000 - val_fp: 928.0000 - val_loss: 0.1360 - val_prc: 0.8008 - val_precision: 0.0766 - val_recall: 0.9390 - val_tn: 44559.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 23/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0563 - accuracy: 0.9268 - auc: 0.9774 - cross entropy: 0.1852 - fn: 89.0000 - fp: 61.0000 - loss: 0.1852 - prc: 0.9814 - precision: 0.9383 - recall: 0.9124 - tn: 971.0000 - tp: 927.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0572 - accuracy: 0.9275 - auc: 0.9765 - cross entropy: 0.1896 - fn: 232.5000 - fp: 137.7500 - loss: 0.1896 - prc: 0.9803 - precision: 0.9422 - recall: 0.9085 - tn: 2464.2500 - tp: 2285.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0574 - accuracy: 0.9273 - auc: 0.9763 - cross entropy: 0.1908 - fn: 378.5714 - fp: 217.8571 - loss: 0.1908 - prc: 0.9801 - precision: 0.9430 - recall: 0.9072 - tn: 3936.8572 - tp: 3658.7144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0576 - accuracy: 0.9269 - auc: 0.9762 - cross entropy: 0.1912 - fn: 527.9000 - fp: 299.3000 - loss: 0.1912 - prc: 0.9801 - precision: 0.9433 - recall: 0.9063 - tn: 5393.3999 - tp: 5043.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0576 - accuracy: 0.9266 - auc: 0.9762 - cross entropy: 0.1913 - fn: 678.3077 - fp: 378.1538 - loss: 0.1913 - prc: 0.9802 - precision: 0.9438 - recall: 0.9058 - tn: 6838.3848 - tp: 6441.1538"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0575 - accuracy: 0.9266 - auc: 0.9762 - cross entropy: 0.1911 - fn: 827.1250 - fp: 454.8750 - loss: 0.1911 - prc: 0.9803 - precision: 0.9444 - recall: 0.9056 - tn: 8272.0625 - tp: 7853.9375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0574 - accuracy: 0.9266 - auc: 0.9763 - cross entropy: 0.1908 - fn: 973.5263 - fp: 531.8947 - loss: 0.1908 - prc: 0.9804 - precision: 0.9447 - recall: 0.9055 - tn: 9717.2109 - tp: 9257.3682"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 28ms/step - Brier score: 0.0573 - accuracy: 0.9267 - auc: 0.9764 - cross entropy: 0.1905 - fn: 1066.1428 - fp: 581.2381 - loss: 0.1905 - prc: 0.9805 - precision: 0.9449 - recall: 0.9055 - tn: 10638.0479 - tp: 10145.0479 - val_Brier score: 0.0266 - val_accuracy: 0.9798 - val_auc: 0.9857 - val_cross entropy: 0.1311 - val_fn: 5.0000 - val_fp: 914.0000 - val_loss: 0.1311 - val_prc: 0.8010 - val_precision: 0.0777 - val_recall: 0.9390 - val_tn: 44573.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 24/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0552 - accuracy: 0.9307 - auc: 0.9762 - cross entropy: 0.1858 - fn: 96.0000 - fp: 46.0000 - loss: 0.1858 - prc: 0.9811 - precision: 0.9522 - recall: 0.9052 - tn: 989.0000 - tp: 917.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0563 - accuracy: 0.9276 - auc: 0.9766 - cross entropy: 0.1875 - fn: 236.0000 - fp: 139.7500 - loss: 0.1875 - prc: 0.9812 - precision: 0.9452 - recall: 0.9076 - tn: 2416.7500 - tp: 2327.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0565 - accuracy: 0.9265 - auc: 0.9767 - cross entropy: 0.1879 - fn: 377.8571 - fp: 232.0000 - loss: 0.1879 - prc: 0.9811 - precision: 0.9430 - recall: 0.9076 - tn: 3866.0000 - tp: 3716.1428"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0565 - accuracy: 0.9263 - auc: 0.9767 - cross entropy: 0.1880 - fn: 521.0000 - fp: 316.4000 - loss: 0.1880 - prc: 0.9810 - precision: 0.9427 - recall: 0.9074 - tn: 5325.8999 - tp: 5100.7002"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0565 - accuracy: 0.9262 - auc: 0.9768 - cross entropy: 0.1881 - fn: 663.5385 - fp: 399.6923 - loss: 0.1881 - prc: 0.9810 - precision: 0.9427 - recall: 0.9074 - tn: 6778.6152 - tp: 6494.1538"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0565 - accuracy: 0.9262 - auc: 0.9768 - cross entropy: 0.1882 - fn: 808.1250 - fp: 482.2500 - loss: 0.1882 - prc: 0.9810 - precision: 0.9427 - recall: 0.9072 - tn: 8232.6875 - tp: 7884.9375"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0565 - accuracy: 0.9263 - auc: 0.9769 - cross entropy: 0.1881 - fn: 950.3684 - fp: 562.1579 - loss: 0.1881 - prc: 0.9810 - precision: 0.9429 - recall: 0.9072 - tn: 9695.4209 - tp: 9272.0527"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 27ms/step - Brier score: 0.0564 - accuracy: 0.9264 - auc: 0.9770 - cross entropy: 0.1879 - fn: 1040.5238 - fp: 611.6667 - loss: 0.1879 - prc: 0.9811 - precision: 0.9431 - recall: 0.9072 - tn: 10623.2861 - tp: 10155.0000 - val_Brier score: 0.0255 - val_accuracy: 0.9802 - val_auc: 0.9862 - val_cross entropy: 0.1263 - val_fn: 5.0000 - val_fp: 895.0000 - val_loss: 0.1263 - val_prc: 0.7927 - val_precision: 0.0792 - val_recall: 0.9390 - val_tn: 44592.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 25/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0534 - accuracy: 0.9287 - auc: 0.9798 - cross entropy: 0.1753 - fn: 102.0000 - fp: 44.0000 - loss: 0.1753 - prc: 0.9831 - precision: 0.9545 - recall: 0.9004 - tn: 980.0000 - tp: 922.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0528 - accuracy: 0.9309 - auc: 0.9800 - cross entropy: 0.1772 - fn: 230.7500 - fp: 122.0000 - loss: 0.1772 - prc: 0.9829 - precision: 0.9507 - recall: 0.9071 - tn: 2478.5000 - tp: 2288.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 6/20\u001b[0m \u001b[32m━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0534 - accuracy: 0.9304 - auc: 0.9794 - cross entropy: 0.1793 - fn: 323.1667 - fp: 177.0000 - loss: 0.1793 - prc: 0.9824 - precision: 0.9491 - recall: 0.9074 - tn: 3468.0000 - tp: 3199.8333"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 9/20\u001b[0m \u001b[32m━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 23ms/step - Brier score: 0.0537 - accuracy: 0.9301 - auc: 0.9791 - cross entropy: 0.1805 - fn: 460.2222 - fp: 258.0000 - loss: 0.1805 - prc: 0.9822 - precision: 0.9481 - recall: 0.9081 - tn: 4933.5557 - tp: 4588.2222"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m12/20\u001b[0m \u001b[32m━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0539 - accuracy: 0.9300 - auc: 0.9789 - cross entropy: 0.1812 - fn: 603.5000 - fp: 332.4167 - loss: 0.1812 - prc: 0.9821 - precision: 0.9481 - recall: 0.9079 - tn: 6403.1665 - tp: 5972.9165"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m15/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━\u001b[0m \u001b[1m0s\u001b[0m 23ms/step - Brier score: 0.0541 - accuracy: 0.9299 - auc: 0.9787 - cross entropy: 0.1817 - fn: 746.0667 - fp: 407.6667 - loss: 0.1817 - prc: 0.9820 - precision: 0.9480 - recall: 0.9078 - tn: 7876.1333 - tp: 7354.1333"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m18/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0542 - accuracy: 0.9298 - auc: 0.9787 - cross entropy: 0.1819 - fn: 889.7222 - fp: 481.7222 - loss: 0.1819 - prc: 0.9819 - precision: 0.9481 - recall: 0.9076 - tn: 9346.0557 - tp: 8738.5000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 29ms/step - Brier score: 0.0543 - accuracy: 0.9297 - auc: 0.9786 - cross entropy: 0.1820 - fn: 1029.3810 - fp: 555.0000 - loss: 0.1820 - prc: 0.9819 - precision: 0.9481 - recall: 0.9075 - tn: 10767.4287 - tp: 10078.6670 - val_Brier score: 0.0245 - val_accuracy: 0.9804 - val_auc: 0.9864 - val_cross entropy: 0.1217 - val_fn: 5.0000 - val_fp: 887.0000 - val_loss: 0.1217 - val_prc: 0.7928 - val_precision: 0.0799 - val_recall: 0.9390 - val_tn: 44600.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 26/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0584 - accuracy: 0.9248 - auc: 0.9747 - cross entropy: 0.1926 - fn: 100.0000 - fp: 54.0000 - loss: 0.1926 - prc: 0.9792 - precision: 0.9439 - recall: 0.9008 - tn: 986.0000 - tp: 908.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0555 - accuracy: 0.9287 - auc: 0.9775 - cross entropy: 0.1844 - fn: 238.2500 - fp: 122.2500 - loss: 0.1844 - prc: 0.9815 - precision: 0.9484 - recall: 0.9051 - tn: 2461.5000 - tp: 2298.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0551 - accuracy: 0.9295 - auc: 0.9779 - cross entropy: 0.1834 - fn: 373.5714 - fp: 197.4286 - loss: 0.1834 - prc: 0.9818 - precision: 0.9486 - recall: 0.9067 - tn: 3938.7144 - tp: 3682.2856"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0548 - accuracy: 0.9300 - auc: 0.9783 - cross entropy: 0.1825 - fn: 509.9000 - fp: 269.8000 - loss: 0.1825 - prc: 0.9820 - precision: 0.9490 - recall: 0.9076 - tn: 5404.0000 - tp: 5080.2998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0544 - accuracy: 0.9304 - auc: 0.9786 - cross entropy: 0.1817 - fn: 652.3846 - fp: 336.4615 - loss: 0.1817 - prc: 0.9823 - precision: 0.9498 - recall: 0.9078 - tn: 6859.6152 - tp: 6487.5386"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0542 - accuracy: 0.9305 - auc: 0.9788 - cross entropy: 0.1811 - fn: 795.5000 - fp: 404.0625 - loss: 0.1811 - prc: 0.9825 - precision: 0.9503 - recall: 0.9079 - tn: 8305.2500 - tp: 7903.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0541 - accuracy: 0.9307 - auc: 0.9789 - cross entropy: 0.1806 - fn: 935.8947 - fp: 471.8947 - loss: 0.1806 - prc: 0.9826 - precision: 0.9507 - recall: 0.9081 - tn: 9758.5264 - tp: 9313.6846"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 27ms/step - Brier score: 0.0540 - accuracy: 0.9308 - auc: 0.9790 - cross entropy: 0.1803 - fn: 1024.8572 - fp: 514.5714 - loss: 0.1803 - prc: 0.9827 - precision: 0.9510 - recall: 0.9082 - tn: 10685.9043 - tp: 10205.1426 - val_Brier score: 0.0237 - val_accuracy: 0.9807 - val_auc: 0.9864 - val_cross entropy: 0.1180 - val_fn: 5.0000 - val_fp: 874.0000 - val_loss: 0.1180 - val_prc: 0.7845 - val_precision: 0.0810 - val_recall: 0.9390 - val_tn: 44613.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 27/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0510 - accuracy: 0.9351 - auc: 0.9819 - cross entropy: 0.1717 - fn: 91.0000 - fp: 42.0000 - loss: 0.1717 - prc: 0.9854 - precision: 0.9594 - recall: 0.9160 - tn: 923.0000 - tp: 992.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 4/20\u001b[0m \u001b[32m━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0535 - accuracy: 0.9293 - auc: 0.9797 - cross entropy: 0.1804 - fn: 238.2500 - fp: 128.5000 - loss: 0.1804 - prc: 0.9827 - precision: 0.9501 - recall: 0.9096 - tn: 2390.2500 - tp: 2363.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 7/20\u001b[0m \u001b[32m━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0535 - accuracy: 0.9295 - auc: 0.9796 - cross entropy: 0.1798 - fn: 374.2857 - fp: 203.8571 - loss: 0.1798 - prc: 0.9827 - precision: 0.9493 - recall: 0.9095 - tn: 3870.7144 - tp: 3743.1428"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m10/20\u001b[0m \u001b[32m━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 22ms/step - Brier score: 0.0531 - accuracy: 0.9301 - auc: 0.9798 - cross entropy: 0.1787 - fn: 507.5000 - fp: 275.5000 - loss: 0.1787 - prc: 0.9828 - precision: 0.9494 - recall: 0.9099 - tn: 5349.7002 - tp: 5131.2998"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m13/20\u001b[0m \u001b[32m━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0530 - accuracy: 0.9305 - auc: 0.9799 - cross entropy: 0.1779 - fn: 643.1539 - fp: 345.0000 - loss: 0.1779 - prc: 0.9830 - precision: 0.9498 - recall: 0.9101 - tn: 6819.9229 - tp: 6527.9229"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m16/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0529 - accuracy: 0.9308 - auc: 0.9800 - cross entropy: 0.1775 - fn: 779.5625 - fp: 415.5625 - loss: 0.1775 - prc: 0.9831 - precision: 0.9500 - recall: 0.9102 - tn: 8295.6875 - tp: 7917.1875"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m19/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 21ms/step - Brier score: 0.0528 - accuracy: 0.9310 - auc: 0.9801 - cross entropy: 0.1772 - fn: 915.7895 - fp: 486.8947 - loss: 0.1772 - prc: 0.9831 - precision: 0.9501 - recall: 0.9103 - tn: 9763.3154 - tp: 9314.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 26ms/step - Brier score: 0.0528 - accuracy: 0.9310 - auc: 0.9801 - cross entropy: 0.1770 - fn: 1002.4762 - fp: 533.0952 - loss: 0.1770 - prc: 0.9832 - precision: 0.9501 - recall: 0.9103 - tn: 10691.4766 - tp: 10203.4287 - val_Brier score: 0.0230 - val_accuracy: 0.9811 - val_auc: 0.9867 - val_cross entropy: 0.1144 - val_fn: 5.0000 - val_fp: 858.0000 - val_loss: 0.1144 - val_prc: 0.7843 - val_precision: 0.0824 - val_recall: 0.9390 - val_tn: 44629.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 28/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0553 - accuracy: 0.9248 - auc: 0.9787 - cross entropy: 0.1808 - fn: 92.0000 - fp: 62.0000 - loss: 0.1808 - prc: 0.9827 - precision: 0.9384 - recall: 0.9113 - tn: 949.0000 - tp: 945.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0546 - accuracy: 0.9256 - auc: 0.9791 - cross entropy: 0.1802 - fn: 277.8000 - fp: 175.4000 - loss: 0.1802 - prc: 0.9826 - precision: 0.9398 - recall: 0.9093 - tn: 2906.8000 - tp: 2784.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0540 - accuracy: 0.9271 - auc: 0.9796 - cross entropy: 0.1788 - fn: 411.2500 - fp: 249.8750 - loss: 0.1788 - prc: 0.9828 - precision: 0.9419 - recall: 0.9099 - tn: 4381.8750 - tp: 4173.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0537 - accuracy: 0.9282 - auc: 0.9798 - cross entropy: 0.1781 - fn: 545.0000 - fp: 320.9091 - loss: 0.1781 - prc: 0.9829 - precision: 0.9435 - recall: 0.9103 - tn: 5858.1816 - tp: 5563.9092"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0534 - accuracy: 0.9289 - auc: 0.9799 - cross entropy: 0.1774 - fn: 680.4286 - fp: 389.6429 - loss: 0.1774 - prc: 0.9830 - precision: 0.9448 - recall: 0.9105 - tn: 7329.2144 - tp: 6960.7144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0532 - accuracy: 0.9294 - auc: 0.9800 - cross entropy: 0.1769 - fn: 816.2941 - fp: 458.9412 - loss: 0.1769 - prc: 0.9831 - precision: 0.9457 - recall: 0.9106 - tn: 8809.7061 - tp: 8347.0586"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step - Brier score: 0.0530 - accuracy: 0.9299 - auc: 0.9801 - cross entropy: 0.1764 - fn: 951.3500 - fp: 527.2500 - loss: 0.1764 - prc: 0.9832 - precision: 0.9465 - recall: 0.9107 - tn: 10281.9502 - tp: 9743.4502"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 26ms/step - Brier score: 0.0530 - accuracy: 0.9300 - auc: 0.9802 - cross entropy: 0.1762 - fn: 992.1905 - fp: 547.8095 - loss: 0.1762 - prc: 0.9832 - precision: 0.9467 - recall: 0.9107 - tn: 10725.5234 - tp: 10164.9521 - val_Brier score: 0.0222 - val_accuracy: 0.9815 - val_auc: 0.9870 - val_cross entropy: 0.1106 - val_fn: 5.0000 - val_fp: 839.0000 - val_loss: 0.1106 - val_prc: 0.7847 - val_precision: 0.0841 - val_recall: 0.9390 - val_tn: 44648.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 29/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0503 - accuracy: 0.9326 - auc: 0.9827 - cross entropy: 0.1660 - fn: 86.0000 - fp: 52.0000 - loss: 0.1660 - prc: 0.9861 - precision: 0.9490 - recall: 0.9184 - tn: 942.0000 - tp: 968.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0499 - accuracy: 0.9359 - auc: 0.9828 - cross entropy: 0.1658 - fn: 252.2000 - fp: 139.2000 - loss: 0.1658 - prc: 0.9855 - precision: 0.9523 - recall: 0.9182 - tn: 2933.8000 - tp: 2818.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0500 - accuracy: 0.9359 - auc: 0.9825 - cross entropy: 0.1666 - fn: 384.1250 - fp: 204.0000 - loss: 0.1666 - prc: 0.9853 - precision: 0.9532 - recall: 0.9174 - tn: 4398.7500 - tp: 4229.1250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0502 - accuracy: 0.9356 - auc: 0.9823 - cross entropy: 0.1672 - fn: 525.2727 - fp: 268.0909 - loss: 0.1672 - prc: 0.9851 - precision: 0.9537 - recall: 0.9160 - tn: 5859.2729 - tp: 5635.3638"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0503 - accuracy: 0.9354 - auc: 0.9822 - cross entropy: 0.1676 - fn: 661.1429 - fp: 334.5000 - loss: 0.1676 - prc: 0.9849 - precision: 0.9540 - recall: 0.9154 - tn: 7326.3569 - tp: 7038.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0503 - accuracy: 0.9353 - auc: 0.9821 - cross entropy: 0.1677 - fn: 795.2353 - fp: 400.7059 - loss: 0.1677 - prc: 0.9849 - precision: 0.9541 - recall: 0.9150 - tn: 8797.7646 - tp: 8438.2939"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0503 - accuracy: 0.9352 - auc: 0.9820 - cross entropy: 0.1677 - fn: 930.4500 - fp: 466.8500 - loss: 0.1677 - prc: 0.9849 - precision: 0.9542 - recall: 0.9147 - tn: 10268.3496 - tp: 9838.3496"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0503 - accuracy: 0.9352 - auc: 0.9820 - cross entropy: 0.1677 - fn: 971.4762 - fp: 486.4762 - loss: 0.1677 - prc: 0.9849 - precision: 0.9542 - recall: 0.9146 - tn: 10711.7617 - tp: 10260.7617 - val_Brier score: 0.0219 - val_accuracy: 0.9813 - val_auc: 0.9866 - val_cross entropy: 0.1085 - val_fn: 5.0000 - val_fp: 846.0000 - val_loss: 0.1085 - val_prc: 0.7853 - val_precision: 0.0834 - val_recall: 0.9390 - val_tn: 44641.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 30/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0512 - accuracy: 0.9365 - auc: 0.9805 - cross entropy: 0.1707 - fn: 91.0000 - fp: 39.0000 - loss: 0.1707 - prc: 0.9844 - precision: 0.9604 - recall: 0.9122 - tn: 972.0000 - tp: 946.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 14ms/step - Brier score: 0.0507 - accuracy: 0.9351 - auc: 0.9812 - cross entropy: 0.1695 - fn: 263.0000 - fp: 137.4000 - loss: 0.1695 - prc: 0.9841 - precision: 0.9542 - recall: 0.9135 - tn: 2954.2000 - tp: 2789.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0506 - accuracy: 0.9351 - auc: 0.9813 - cross entropy: 0.1695 - fn: 390.5000 - fp: 208.1250 - loss: 0.1695 - prc: 0.9842 - precision: 0.9535 - recall: 0.9142 - tn: 4425.7500 - tp: 4191.6250"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0506 - accuracy: 0.9352 - auc: 0.9814 - cross entropy: 0.1694 - fn: 520.3636 - fp: 276.1818 - loss: 0.1694 - prc: 0.9842 - precision: 0.9535 - recall: 0.9146 - tn: 5881.3638 - tp: 5610.0908"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0504 - accuracy: 0.9354 - auc: 0.9816 - cross entropy: 0.1689 - fn: 649.5714 - fp: 339.7857 - loss: 0.1689 - prc: 0.9844 - precision: 0.9539 - recall: 0.9148 - tn: 7345.5000 - tp: 7025.1431"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0503 - accuracy: 0.9356 - auc: 0.9817 - cross entropy: 0.1686 - fn: 777.6470 - fp: 404.4706 - loss: 0.1686 - prc: 0.9844 - precision: 0.9541 - recall: 0.9150 - tn: 8820.1172 - tp: 8429.7646"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0503 - accuracy: 0.9357 - auc: 0.9817 - cross entropy: 0.1685 - fn: 906.0000 - fp: 472.0000 - loss: 0.1685 - prc: 0.9845 - precision: 0.9541 - recall: 0.9151 - tn: 10297.7998 - tp: 9828.2002"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0503 - accuracy: 0.9357 - auc: 0.9817 - cross entropy: 0.1684 - fn: 944.7143 - fp: 492.0000 - loss: 0.1684 - prc: 0.9845 - precision: 0.9541 - recall: 0.9152 - tn: 10743.7139 - tp: 10250.0479 - val_Brier score: 0.0214 - val_accuracy: 0.9813 - val_auc: 0.9868 - val_cross entropy: 0.1059 - val_fn: 5.0000 - val_fp: 849.0000 - val_loss: 0.1059 - val_prc: 0.7861 - val_precision: 0.0832 - val_recall: 0.9390 - val_tn: 44638.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 31/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0493 - accuracy: 0.9390 - auc: 0.9820 - cross entropy: 0.1702 - fn: 83.0000 - fp: 42.0000 - loss: 0.1702 - prc: 0.9843 - precision: 0.9571 - recall: 0.9185 - tn: 987.0000 - tp: 936.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0493 - accuracy: 0.9384 - auc: 0.9824 - cross entropy: 0.1674 - fn: 263.6000 - fp: 116.6000 - loss: 0.1674 - prc: 0.9849 - precision: 0.9599 - recall: 0.9145 - tn: 2963.3999 - tp: 2800.3999"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0495 - accuracy: 0.9377 - auc: 0.9824 - cross entropy: 0.1678 - fn: 395.3750 - fp: 183.0000 - loss: 0.1678 - prc: 0.9849 - precision: 0.9589 - recall: 0.9145 - tn: 4420.6250 - tp: 4217.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0494 - accuracy: 0.9376 - auc: 0.9825 - cross entropy: 0.1675 - fn: 525.1818 - fp: 246.0909 - loss: 0.1675 - prc: 0.9850 - precision: 0.9586 - recall: 0.9147 - tn: 5885.5454 - tp: 5631.1816"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0493 - accuracy: 0.9376 - auc: 0.9826 - cross entropy: 0.1669 - fn: 652.9286 - fp: 307.5714 - loss: 0.1669 - prc: 0.9851 - precision: 0.9585 - recall: 0.9149 - tn: 7361.7856 - tp: 7037.7144"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0492 - accuracy: 0.9377 - auc: 0.9827 - cross entropy: 0.1666 - fn: 781.1177 - fp: 369.8235 - loss: 0.1666 - prc: 0.9851 - precision: 0.9583 - recall: 0.9150 - tn: 8855.4121 - tp: 8425.6475"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0491 - accuracy: 0.9376 - auc: 0.9828 - cross entropy: 0.1664 - fn: 913.2500 - fp: 433.0000 - loss: 0.1664 - prc: 0.9852 - precision: 0.9582 - recall: 0.9149 - tn: 10339.5000 - tp: 9818.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step - Brier score: 0.0491 - accuracy: 0.9375 - auc: 0.9828 - cross entropy: 0.1663 - fn: 953.2381 - fp: 452.3810 - loss: 0.1663 - prc: 0.9852 - precision: 0.9581 - recall: 0.9148 - tn: 10786.8096 - tp: 10238.0479 - val_Brier score: 0.0209 - val_accuracy: 0.9814 - val_auc: 0.9870 - val_cross entropy: 0.1031 - val_fn: 5.0000 - val_fp: 844.0000 - val_loss: 0.1031 - val_prc: 0.7774 - val_precision: 0.0836 - val_recall: 0.9390 - val_tn: 44643.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 32/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 4ms/step - Brier score: 0.0488 - accuracy: 0.9399 - auc: 0.9839 - cross entropy: 0.1756 - fn: 82.0000 - fp: 41.0000 - loss: 0.1756 - prc: 0.9841 - precision: 0.9560 - recall: 0.9156 - tn: 1035.0000 - tp: 890.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 16ms/step - Brier score: 0.0490 - accuracy: 0.9386 - auc: 0.9837 - cross entropy: 0.1686 - fn: 252.2000 - fp: 126.8000 - loss: 0.1686 - prc: 0.9850 - precision: 0.9559 - recall: 0.9159 - tn: 3012.3999 - tp: 2752.6001"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0489 - accuracy: 0.9386 - auc: 0.9837 - cross entropy: 0.1665 - fn: 379.0000 - fp: 188.1250 - loss: 0.1665 - prc: 0.9853 - precision: 0.9565 - recall: 0.9164 - tn: 4475.6250 - tp: 4173.2500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0489 - accuracy: 0.9384 - auc: 0.9836 - cross entropy: 0.1656 - fn: 510.9091 - fp: 249.9091 - loss: 0.1656 - prc: 0.9854 - precision: 0.9567 - recall: 0.9161 - tn: 5955.0908 - tp: 5572.0908"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0488 - accuracy: 0.9381 - auc: 0.9836 - cross entropy: 0.1648 - fn: 647.0714 - fp: 309.6429 - loss: 0.1648 - prc: 0.9855 - precision: 0.9570 - recall: 0.9155 - tn: 7440.4287 - tp: 6962.8569"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0488 - accuracy: 0.9379 - auc: 0.9836 - cross entropy: 0.1643 - fn: 781.8235 - fp: 371.0588 - loss: 0.1643 - prc: 0.9855 - precision: 0.9571 - recall: 0.9151 - tn: 8916.1172 - tp: 8363.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0487 - accuracy: 0.9378 - auc: 0.9836 - cross entropy: 0.1640 - fn: 913.6000 - fp: 432.8500 - loss: 0.1640 - prc: 0.9856 - precision: 0.9572 - recall: 0.9150 - tn: 10385.9502 - tp: 9771.5996"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 25ms/step - Brier score: 0.0487 - accuracy: 0.9377 - auc: 0.9836 - cross entropy: 0.1640 - fn: 953.1905 - fp: 451.4286 - loss: 0.1640 - prc: 0.9856 - precision: 0.9572 - recall: 0.9150 - tn: 10828.9043 - tp: 10196.9521 - val_Brier score: 0.0206 - val_accuracy: 0.9813 - val_auc: 0.9872 - val_cross entropy: 0.1010 - val_fn: 5.0000 - val_fp: 849.0000 - val_loss: 0.1010 - val_prc: 0.7774 - val_precision: 0.0832 - val_recall: 0.9390 - val_tn: 44638.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 33/1000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/20\u001b[0m \u001b[32m━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - Brier score: 0.0474 - accuracy: 0.9380 - auc: 0.9833 - cross entropy: 0.1602 - fn: 83.0000 - fp: 44.0000 - loss: 0.1602 - prc: 0.9857 - precision: 0.9543 - recall: 0.9171 - tn: 1003.0000 - tp: 918.0000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 5/20\u001b[0m \u001b[32m━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 15ms/step - Brier score: 0.0482 - accuracy: 0.9374 - auc: 0.9831 - cross entropy: 0.1619 - fn: 249.6000 - fp: 134.4000 - loss: 0.1619 - prc: 0.9858 - precision: 0.9541 - recall: 0.9184 - tn: 2944.2000 - tp: 2815.8000"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m 8/20\u001b[0m \u001b[32m━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 17ms/step - Brier score: 0.0480 - accuracy: 0.9379 - auc: 0.9834 - cross entropy: 0.1609 - fn: 377.1250 - fp: 191.8750 - loss: 0.1609 - prc: 0.9862 - precision: 0.9557 - recall: 0.9184 - tn: 4392.2500 - tp: 4254.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m11/20\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0479 - accuracy: 0.9380 - auc: 0.9835 - cross entropy: 0.1604 - fn: 506.8182 - fp: 251.5455 - loss: 0.1604 - prc: 0.9863 - precision: 0.9565 - recall: 0.9181 - tn: 5855.3638 - tp: 5674.2729"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m14/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0478 - accuracy: 0.9380 - auc: 0.9836 - cross entropy: 0.1602 - fn: 633.8571 - fp: 315.7143 - loss: 0.1602 - prc: 0.9863 - precision: 0.9566 - recall: 0.9181 - tn: 7318.0000 - tp: 7092.4287"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m17/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━\u001b[0m \u001b[1m0s\u001b[0m 18ms/step - Brier score: 0.0478 - accuracy: 0.9380 - auc: 0.9836 - cross entropy: 0.1603 - fn: 761.1177 - fp: 380.8824 - loss: 0.1603 - prc: 0.9863 - precision: 0.9566 - recall: 0.9180 - tn: 8785.7646 - tp: 8504.2354"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 19ms/step - Brier score: 0.0479 - accuracy: 0.9378 - auc: 0.9836 - cross entropy: 0.1604 - fn: 891.4000 - fp: 447.3000 - loss: 0.1604 - prc: 0.9863 - precision: 0.9565 - recall: 0.9178 - tn: 10258.5498 - tp: 9906.7500"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m20/20\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 25ms/step - Brier score: 0.0479 - accuracy: 0.9378 - auc: 0.9836 - cross entropy: 0.1604 - fn: 931.0476 - fp: 467.4762 - loss: 0.1604 - prc: 0.9863 - precision: 0.9565 - recall: 0.9177 - tn: 10702.9521 - tp: 10329.0000 - val_Brier score: 0.0203 - val_accuracy: 0.9813 - val_auc: 0.9874 - val_cross entropy: 0.0994 - val_fn: 5.0000 - val_fp: 849.0000 - val_loss: 0.0994 - val_prc: 0.7777 - val_precision: 0.0832 - val_recall: 0.9390 - val_tn: 44638.0000 - val_tp: 77.0000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 33: early stopping\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Restoring model weights from the end of the best epoch: 23.\n"
]
}
],
"source": [
"resampled_model = make_model()\n",
"resampled_model.load_weights(initial_weights)\n",
"\n",
"# Reset the bias to zero, since this dataset is balanced.\n",
"output_layer = resampled_model.layers[-1]\n",
"output_layer.bias.assign([0])\n",
"\n",
"resampled_history = resampled_model.fit(\n",
" resampled_ds,\n",
" # These are not real epochs\n",
" steps_per_epoch=20,\n",
" epochs=10*EPOCHS,\n",
" callbacks=[early_stopping()],\n",
" validation_data=(val_ds))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "UuJYKv0gpBK1"
},
"source": [
"### Re-check training history"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:26:59.875488Z",
"iopub.status.busy": "2024-08-20T01:26:59.874811Z",
"iopub.status.idle": "2024-08-20T01:27:00.398512Z",
"shell.execute_reply": "2024-08-20T01:27:00.397800Z"
},
"id": "FMycrpJwn39w"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_metrics(resampled_history)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "bUuE5HOWZiwP"
},
"source": [
"### Evaluate metrics"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:27:00.402488Z",
"iopub.status.busy": "2024-08-20T01:27:00.402235Z",
"iopub.status.idle": "2024-08-20T01:27:01.059784Z",
"shell.execute_reply": "2024-08-20T01:27:01.059097Z"
},
"id": "C0fmHSgXxFdW"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/90\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m13s\u001b[0m 151ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m50/90\u001b[0m \u001b[32m━━━━━━━━━━━\u001b[0m\u001b[37m━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 1ms/step "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m90/90\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
"\u001b[1m 1/28\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1s\u001b[0m 41ms/step"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m28/28\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
"\u001b[1m28/28\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step\n"
]
}
],
"source": [
"train_predictions_resampled = resampled_model.predict(train_features, batch_size=BATCH_SIZE)\n",
"test_predictions_resampled = resampled_model.predict(test_features, batch_size=BATCH_SIZE)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:27:01.063422Z",
"iopub.status.busy": "2024-08-20T01:27:01.062862Z",
"iopub.status.idle": "2024-08-20T01:27:04.026261Z",
"shell.execute_reply": "2024-08-20T01:27:04.025517Z"
},
"id": "FO0mMOYUDWFk"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"loss : 0.129319429397583\n",
"compile_metrics : 0.129319429397583\n",
"\n",
"Legitimate Transactions Detected (True Negatives): 55717\n",
"Legitimate Transactions Incorrectly Detected (False Positives): 1143\n",
"Fraudulent Transactions Missed (False Negatives): 9\n",
"Fraudulent Transactions Detected (True Positives): 93\n",
"Total Fraudulent Transactions: 102\n"
]
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"resampled_results = resampled_model.evaluate(test_features, test_labels,\n",
" batch_size=BATCH_SIZE, verbose=0)\n",
"for name, value in zip(resampled_model.metrics_names, resampled_results):\n",
" print(name, ': ', value)\n",
"print()\n",
"plot_cm(test_labels, test_predictions_resampled)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_xYozM1IIITq"
},
"source": [
"### Plot the ROC"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:27:04.029781Z",
"iopub.status.busy": "2024-08-20T01:27:04.029531Z",
"iopub.status.idle": "2024-08-20T01:27:04.380742Z",
"shell.execute_reply": "2024-08-20T01:27:04.380049Z"
},
"id": "fye_CiuYrZ1U"
},
"outputs": [
{
"data": {
"image/png": 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TTwUAAACAVsLU2Ul5ebnefPNNvf322xo2bJikytWwuXPn6sknn9TUqVOVk5MT1uftt9/WSSedpB49etQ5tt1ur9YXAAAAAMzA1Imaz+eT3++X0xl+p6mkpCR98skn1drv2LFD7733nmbNmlXv2D/++KNyc3PldDo1ePBg3X///erSpUut7T0ejzyeqgdoulwuSZUXLXu93khfUo329W/sOIgcc24M5t0YzLsxmvu8B4KB0LbP6zPN6/B5faHtYDBYLa7mPu/NFfNuDCPmvZ2znRSs/LO1vt9N9botwWAw2CRHaqAhQ4YoISFBs2fPVocOHfTqq69q3Lhx6tWrl9avD38Q54MPPqgHHnhAeXl51ZK7/b3//vsqKSnRwQcfrO3bt2vKlCnatm2b1qxZo7S0tBr73HPPPZoyZUq1+tmzZys5OblxLxIAAJN5ZaNVX+ysvJT9zkE+dUgyOKDflARK9IDrAUnSIfZDdHHqxQZHBKC1KSsr00UXXaSioiKlp6fH7TimT9Q2bdqkyy+/XMuWLZPNZtMRRxyhPn36aNWqVVq3bl1Y2759+2rkyJGaMWNGVMfYu3evunbtqunTp+uKK66osU1NK2qdO3fWrl27Gv0Geb1eLVy4UCNHjpTD4WjUWIgMc24M5t0YzLsxmvu83/7fNXrr6zxJ0oIbj1OP9ikGR1SpsLxQI98aKUk68aATNX3Y9LD9zX3emyvm3RjMuzEKCwvVsWPHuCdqpj71UZJ69uyppUuXqrS0VC6XSx07dtT5559f7Rq0jz/+WOvXr9drr70W9TEyMzPVp08fbdy4sdY2iYmJSkxMrFbvcDhi9hcjlmMhMsy5MZh3YzDvxoh03ovKvFr+U6HM8vvTvL3u0LbdYTfNZ8fuq/rqYrFYao2Lz7sxmHdjMO9Nq6nm2vSJ2j4pKSlKSUnRnj17tGDBAj344INh+5977jkdeeSRGjhwYNRjl5SUaNOmTbrkkktiFS4AABGr8AU04pGl2lnsqb9xKzd73WyjQwCAJmH656gtWLBA8+fP1+bNm7Vw4UKddNJJ6tu3r8aPHx9q43K59Prrr+vKK6+scYzhw4friSeeCJVvvfVWLV26VFu2bNFnn32ms88+WzabTRdeeGHcXw8AAAf6ZXepaZO0dKdduRkmuUBN0hbXltB2W2db4wIBWqkpy6do4kcTNWV59Xs3ILZMv6JWVFSkyZMna+vWrWrbtq3Gjh2r++67L2zJcc6cOQoGg7UmWps2bdKuXbtC5a1bt+rCCy9UYWGh2rdvr6FDh2rFihVq37593F8PAAD1uXNMX6NDkCRZLRad1DdbSQk2o0Op0eWHXm50CECrs2zrMhWUFSg7OdvoUFo80ydq5513ns4777w621x99dW6+uqra92/ZcuWsPKcOXNiERoAADF37pEH6ephPY0Oo1lIsCUYHQIAxI3pT30EAAAAgNaGRA0AAAAATIZEDQAAAABMhkQNAAAAAEyGRA0AAAAATIZEDQAAAABMhkQNAAAAAEzG9M9RAwC0PnvLKlTs9sX9OLvdhaoIeOIyts/n1U9lu7Vy20bZ7Y46227dUyaLY7ckqSyQoK3FW+MSU0tQ7is3OgSgVRvTfYxcFS6lJ6QbHUqLR6IGADCVl1f8rL+98738gWBcj5PY4R0ltP0srseQpOeXRtYutVfln8vc0rL/xi8eAGiMSUdNMjqEVoNEDQBgKv/7elvckzRJcmSsivsxEEeBBJ35+Feae/3Jyk53hqrnfLlV/1hl072bHpM3/X3JWvOKabIlRyvGvxFWN+Klq1XgXVvvoQdlnqIXz/lrWN1hzw+NKOyJA+/RZUeOCJX/vWqRpn9zT0R9v738k7Dypf+dqtV759fbL9vRT4sueTqs7tgX/qCyYH69fUd3ukQPjb4mVF5XsFXnv3tBjW2DwaDueumhUPmJk/6lYd37h8r3LnlZb2x+qt5jOpShVZe/F1Z36uyb9Ku7/r+zB6cO0+vnTQurG/TccAUs9a+cX9n3Nt045MxQ+e21n+uuFZElJQvPe08dUjNC5evmPqJPdr5Zb78MW3d9PO6lsLrjZ12iIv/mevsObT9Wj50yIVTeUVKkkf85NaJ4/37swzqz3zGh8uOfva1nf3iojh6VrMFErb5icVjdtHnr9M7qvHr7ntQ3W/efMyCs7vQZn2hncf3vzeQxfXXmoE6h8qadJbr4mc/r7SdJ70w4LuzfiNmf/6LHF/9Yb7/uWSl69epjw+pumvO1Pv9pt3zukoiO3VgkagAAU/EHq5K0Mwbmxu04yyok/2/b2dZj62xbmx0uj3z+QK377VapQ3qSZKmq21nsUYWv9j77HJyTpoNz0kJlnz+oed9tjyiu43u3V5uUqtMt8/a6tXLL7nr72W1WjRmQE1a3+pe9+mV3Wb19czOTdFS3NmF1H3y/Q26vv5YeVQZ1zlSXdsmhcrHbpyU/FNTeIWiV1zVIxaXBsM+LJJVV+FRUYVFy6jzZHDtrHcLjS6pWV+ZzKWgrqjfeUm/1L2mR9JOkcn9FtXKkfWuKI5K+ZT5XtTpPoEhBewSvtSL8vfcGfHUec/93o8IffvpyaUV5RPHW9JGJ9L0p8RZXq/NZi2SpJWEPi8/rDiu7fZG/N8Fg+N/p4orI3ptyf/U25f6iiPoWV4R/DoPBQMTxun3hn8NSrzuivr5AYrW6ojKv8l3uGlof0K68olrdzmJPRH3LK8I/FP5AMKJ+kmr8NyKSvmnO6mnS7tIK5bvcCniqv5Z4IFEDAJjW4xceHrexj37FqnKf1Cuzl94685kGjXHstMXKd7lltUjZac6wfUEF1d5WrreuOUUOR1XSdOWsL7VmW/Uvzgc6vWN3XXl8j1C5xOPTZ8sjO4/yxgFHacBBVb/dX7xuhzauWVNvv+REmx4cdmJY3bR56/TOL/X/tvyYg7J1/7Dw35av++YT7Syp/wvyhd2r/7b865X1/LbcJildslksYdXJCXZlJAQVtFdUJg1BiyyB6tfSJFozqtUl29NV4q1ef6AUR2q1Oou//n6SlGRLqFaOtG9NcVhK6++b7Kj59fv99V/vl5KQHFZ2WO21xhsMBmXZ7/1IsIV/zUxJSIrotTpU83tjcdffNzUprVqdPZChQLD+z2GKI/zvsNMe+XtjsYTfny8tITWivkm26m2SbBmqiKBvWkL459BisUYcr9Me/jlMcTgj6msLVk/UMpIdykl31tD6gHZJCdXq2qdVH68mSQm28DisloiOKdX8b0QkfbNSq8fWNiVBOelO+dw+/RrR0RvHEgwG439+SQvkcrmUkZGhoqIipac37mJKr9erefPmacyYMWE/zBE/zLkxmHdjNLd5P/ufn+rrX/ZKkrY8ENlpPA1x9CtHq9xX/lui9laDxtiXqOWkO7XizuFh+5rbvLcU++b9cc/jKigvUHZythafu7j+jmgUPu/GYN6NUVhYqKysrJjkAXVhRQ0AgAa68vjuKnb7ajxFBsa6asBV8gQ8SnYk198YAEyInywAADTQ/qcmwlzG9hrLCgOAZo0HXgMAAACAyZCoAQAAAIDJcOojAAANVOLxhe50l5rIj1Qz2Vm+U9YKq2wWm9ontzc6HACIGj9VAABooBEPL631ro8w1iXzL+GujwCaNU59BAAAAACTYUUNABBzBcVuXffyV9qwozjqviUeX0TtZq6eqf+s/4+8AW/Ux5Ckcl/9D/sFAMAoJGoAgJh795vtWvnznkaNkVbHNV+l3lI9/e3TCgQDjTqGJKUlpDV6DAAAYo1EDQAQc+Vef2i7Q3qiUqK80Uai3aYrhnavdb/X7w0laUn2JHVI7tCgONMT0nXdoOsa1BcAgHgiUQMAxNXUswZoZL+GJVKR+F3O7zRz+My4jQ8AgBG4mQgAAAAAmAyJGgAAAACYDIkaAAAAAJgMiRoAAAAAmAw3EwEAoIGeufQoVfgDSrDxe0+zeWr4U7JYLbJZbUaHAgANQqIGAEADDTgow+gQUItu6d3kcDiMDgMAGoxfAQIAAACAyZCoAQAAAIDJcOojADQjpd5SPf7V49q0d1PEfQLBgApLCvX24rdltcT+93NF5V7lFZXLHwiG6jzegJK6+CVJT/7wml77NSGmx/QGvDEdr6EWr9shtzcgp8Oq4YfE76HeiN77W96XN+iV0+7UqT1ONTocAIgaiRoANCPvb35fs3+Y3aC+P+34KcbRHGD/HDBRsidWbv5YLKk4fod1WI27Dukvb61RvsutnHQniZrJPPb1YyooL1B2cjaJGoBmiVMfAaAZ2e3ebXQIppKekK5zep9jdBgAAMQcK2oA0Ew9fMLDOv6g4+tt5/V6tWDBAo0ePToud8E7/sEl2lXsUccMp+bdGB6PMyG+t0Z3WB2yW/lRBgBoefjpBgDNVKItUUn2pHrb2YN2JVgSlGRPksMe+0TNEkyQgkFZlag2yakxHx8AgNaIUx8BAAAAwGRI1AAAAADAZEjUAAAAAMBkSNQAAAAAwGRI1AAAAADAZLjrIwAADZScaFNqol3JifF9DAGi1y6pnWSRspKyjA4FABqERA0AgAb6cNKJRoeAWrxyyitxeW4gADQVEjUAhvm1+FfN3TRX5b5yo0NpNr7Z+U2j+i/5oUDLfyqMUTSVSty+mI4HAABI1AAY6I5ld+jbXd8aHUazZbFYomq/eVepxv/7yzhFI0UZDgAAqAOJGgDD/Fz8s9EhNFtpCWma8MFkSfVnRzcPuEvtJP28u0ySZEveJGfuaxEdp3TjnWHlhKxFcmR+UWPbvRaLDnv+bklStqOfFl3ydNj+Y1/4g8qC+fUec3SnS/TQ6GtC5XUFW3X+uxdEFO8TJ/1Lw7r3D5XvXfKy3tj8VL39HMrQqsvfC6s7dfZN+tW9qs5+FotFZ/c+VfcMvSOs/vS3TleZt0xut1uPv/V4rW/T3cferRM6nxAqf1/4vW788MZ645Wkd856RymOlFB51vez9OLaF+vt169tP80YPiOs7obFN2jt7rX19r2036Ua139cqFzqLdUZ/zsjongfP/lx9W9X9d4s/XWp7l1xb739ku3Jmnv23LC6h1c+rHmb59XcISi53W7NmjdLM4bPUKfUThHFBwBmQ6IGwHAdkjvowWEPGh1GNXd8fIe2l26vVv/IiY+orbNtqDx/83y9uv7VesfLTc3V/UPvD6v707y/qdy6pd6+ByUM1n0n/ylU7tu2r46ZfUy9/SSp3FcRXmHxy+pwRdT39T8NDivf9fESbQvU3jf4259lvuptPIEiBe1F9R6ztKIsrOwN+BS01d9Pkir84adhllaUR9TX669eV+Zz1ds3KOnzn7fpMfePumlE71D9zvKdKvWWSpJc5bXPl9vvPiAOrwrKCuqNV5KCwWBYudRbGlHfnJScanW7Pbsj6rvvNe0fQ6Txev3esLLb746o7/7J6D6uCle9fbOCWXp45cPqlNpJk46aFFGMAGAmJGoADOe0O3VEhyOMDqMaf7Dy27vVYg27c9zA9gPVPrl9qLypaJOyk7PrHe+g1IOqvc50e0e5vXvq7ds+sUu1vhZ/Rr39JCnJniBpv4QgaFPQlyFrBKcq/q5b27By9leZyttb/3GTHenV6hKtGfL7678eMSUhOazssNojfq0JtvAfaykJSRH1dah6m2R7uizu+vvuLrOp92GpYXXtk9orxZ4it9stp9NZ64qa0+YMj8PmiOizJFU/9TXFkRJR37aJbWusi6TvgUmTxWKJOF6HLfzGHk6bM6K+yfbkanXpCem19/1tRa2kokQb927UKd1OiSg+ADAbS/DAX8khIi6XSxkZGSoqKlJ6evUvJNHwer2aN2+exowZwx2qmghzbowD533onKEq8hSpa3pXvXv2u0aHV83w14eroKxA2cnZWnzuYqPDabB9857c63e66qWvJUm3jOgTtgKE2OPfGWMw78Zg3o3BvBujsLBQWVlZMckD6sKKGgA0sQufXqFdJR5lpSbq1auPNTocAABgQiRqANDENu8qVb7LrWJuaw8AAGphNToAAAAAAEA4VtQAoBbPjnpW/oBfNqvN6FAAAEArQ6IGALXontHd6BAAAEArxamPAAAAAGAyrKgBaJRgMKhVO1ZF9OBav9+vbyq+kXWLVTabTRX+inr7GOH7vCJtLCiJ2/jlvz1dudzr19urt8XtOPv4/X6t3mVRgq3+57UBAABzIFED0CgvrX1JD618KKo+r3/2epyiabyP1hfoshe+lCTZ01fLYq1QMJAgn2tQzI9VVO7VTXNWx3zcmtmkH7c00bEAAEBjkagBaJRvdn7T6DH6tu0bg0hi46tf9oa2E7PnyepwKeBNj0uiZqT+ufF7QCcAAGg8EjUAMXPdwOuUnlh7AuD3+7V27Vr169dPNlvlnRRTHaka0XVEU4UYleQEu9xBKd3p0K2n94vZuNMXblCx26c0p10TR/aJ2bi1OXDe+3RI05Ce7eJ+XAAA0HAkagBi5uzeZysnJafW/V6vV/M2zdOYg8fI4XA0YWQN43RY5a6QkhNtGn9c7O4AmWi3qazCp+QEuy46pkvMxq2N1+vVvD3fa8zgrs1i3gEAAIkaADS5pkjOAABA88bt+QEAAADAZEjUAAAAAMBkOPURAJpYgcstfzAom8Wi7HSn0eEAAAATIlEDgCZ2xhOfKt/lVk66UyvuHG50OAAAwIQ49REAAAAATIYVNQCoRbqjrRLsVmUlZRkdCgAAaGVI1AA0SCAY0C+uX1TqLY2qX5lP2rSzVHa7Of/52VNaEdr+82FPaVif9gZGAwAAWitzflMCYGr+gF8XvHeBftj9Q1T9PtqwU3ettMn35adxigwAAKBl4Bo1AFHbVLSpWpKWbE9WekJ6nf0WfF8gX9ASz9BiKjczyegQAABAK8WKGoCoBYPB0Ha39G46osMROqXbKUp2JNfZL7Bfv1H9OijN6YhbjI01rE+WemWnGh0GAABopUjUADTK73J+p7sH3x11v9tP6Wv6RGjK8ikq8hQpIzFDfxv8N6PDAQAArQiJGgDUYtnWZSooK1B2crbRoQAAgFaGa9QAAAAAwGRYUQOAJvbKVcfIHwjKZm0+N1YBAABNi0QNAJpYz/bmvjYPAAAYj1MfAQAAAMBkSNQAAAAAwGQ49REAmtjbq7epvMKvpASbzhzUyehwAACACZGoAUATu3/eD8p3uZWT7iRRAwAANSJRAxAydcVUzd00V4FgoM52++//z5e/ava89yMav8JX97gAAACoRKIGQJKUX5qv19a/FnW/Cq9TFd7oEjCLRUp3mv+fnzHdx8hV4VJ6QrrRoQAAgFbG9N+UiouLddddd+mtt95SQUGBDj/8cD322GP63e9+J0m67LLLNGvWrLA+o0eP1vz58+scd+bMmXrooYeUn5+vgQMHasaMGTr66KPj9joAs/P4PaHtNEeaclJz6mzv9QX1Y55D3j3HKM1pV6fMpHqPEQwGVVJcrIuG9lF2urPRMUdr6a9Lde+Ke+ttl2xP1tyz52rSUZNCddPmrdM7q/Pq7XtS32zdf86AsLrTZ3yincVV81tQ7I4iagAA0BqZPlG78sortWbNGr300kvKzc3Vyy+/rBEjRmjt2rXq1Kny2o5TTjlFL7zwQqhPYmJinWO+9tprmjhxop566ikdc8wxevTRRzV69GitX79e2dnZcX09QHNwYucTNe34aXW2+XV3mY5/cIkk6aT+2Xr8wsPrHdfr9WrevHkac3z3mMQZLbffrYKygnrbpThSqtUVlXmV76o/wSoqr6hWt7PYU2PflERbveMBAIDWydSJWnl5ud588029/fbbGjZsmCTpnnvu0dy5c/Xkk09q6tSpkioTs5ycun/7v7/p06frqquu0vjx4yVJTz31lN577z09//zzuuOOO2L/QgCYgtPmVHZy/b+MSbYnV6vLSHYoJ4JVwIykhGp17dOq//IoJdGmSaMOrnc8AADQOpk6UfP5fPL7/XI6w78cJSUl6ZNPPgmVP/roI2VnZ6tNmzY6+eSTNXXqVLVr167GMSsqKrRq1SpNnjw5VGe1WjVixAgtX7681lg8Ho88nqpTl1wul6TKFQKv19ug17fPvv6NHQeRY86r83l9oe1AIFDv3Hh9VfsjaS8ZP+9DcoZo/ll1nxa9z8n/WKIdxR51SEvUgpuG6raRvXTbyF4R9T3w9f33T8dE3DYejJ731op5Nwbzbgzm3RjMuzGaar4twWAw2CRHaqAhQ4YoISFBs2fPVocOHfTqq69q3Lhx6tWrl9avX685c+YoOTlZ3bt316ZNm3TnnXcqNTVVy5cvl81W/bSivLw8derUSZ999pkGDx4cqr/99tu1dOlSff755zXGcc8992jKlCnV6mfPnq3k5Oq/fQeam13+XXq0+FFJ0iDHIP0h5Q91ti90S/d+Xfm7niPaBTSuT8u6o+Pdq2wqqrAoIyGoe4/0Gx0OAAAwibKyMl100UUqKipSenr8bjhm6hU1SXrppZd0+eWXq1OnTrLZbDriiCN04YUXatWqVZKkCy64INR2wIABOuyww9SzZ0999NFHGj58eMzimDx5siZOnBgqu1wude7cWaNGjWr0G+T1erVw4UKNHDlSDoejsaEiAsx5db+4ftGj7z4qSerUqZPGDBlTZ/tf95Tp3q8rV7Zzc3M1Zsxh9R7DyHlfu3utvH6vHDaH+rXtV2/7ad8vVVGFR06nU2PGnNAEEcYPn3djMO/GYN6Nwbwbg3k3RmFhYZMcx/SJWs+ePbV06VKVlpbK5XKpY8eOOv/889WjR48a2/fo0UNZWVnauHFjjYlaVlaWbDabduzYEVa/Y8eOOq9zS0xMrPEmJQ6HI2Z/MWI5FiLDnFexO6r+ObBarfXOi8NetT+S9mF9DZj3icsmqqCsQNnJ2Vp87uJ621tkCf3ZUj4jfN6Nwbwbg3k3BvNuDOa9aTXVXFub5CgxkJKSoo4dO2rPnj1asGCBzjzzzBrbbd26VYWFherYsWON+xMSEnTkkUdq8eKqL2qBQECLFy8OOxUSAAAAAIxi+kRtwYIFmj9/vjZv3qyFCxfqpJNOUt++fTV+/HiVlJTotttu04oVK7RlyxYtXrxYZ555pnr16qXRo0eHxhg+fLieeOKJUHnixIl65plnNGvWLK1bt07XXnutSktLQ3eBBAAAAAAjmf7Ux6KiIk2ePFlbt25V27ZtNXbsWN13331yOBzy+Xz69ttvNWvWLO3du1e5ubkaNWqU/v73v4edprhp0ybt2rUrVD7//PO1c+dO3X333crPz9egQYM0f/58dejQwYiXCAAAAABhTJ+onXfeeTrvvPNq3JeUlKQFCxbUO8aWLVuq1U2YMEETJkxobHhAs1Thr9DDKx/Wut3rQnVuX9UDmZdu2Kk/rPmszjE8vpZ1l0cAAAAzMX2iBiD2Pvr1I83+YXat+3cV+7Utf0/E4yXYTX8WNQAAQLPCtyugFdrr2VvrvoA3Xd6ioyIeq0N6os7/XecYRAUAAIB9WFEDWrl7h9yrM3qeIUn617JNenD+BkkW/fPiIzS6f+2PrNjHapEsFkuco2x69519qNzegJwOfp8FAACaHoka0MpZLVbZrLbftm3Sb88Ps1ossllbXgIWqeGHcHMhAABgHH5VDAAAAAAmw4oagFbhnbPeUTAYbJGnaQIAgJaHRA1Aq5DiSImq/Xdbi1ThDyjBZtWAgzLiFBUAAEDNSNQAoAZXvbhS+S63ctKdWnHncKPDAQAArQzXqAEAAACAybCiBqBVmPX9LJV6S5XiSNG4/uOMDgcAAKBOJGoAWoUX176ogrICZSdnk6gBAADTI1EDmqEvt+zW+9/lKxAMRt23IlCixcVPhsr/+3qbvl77vSTpu21FMYsRAAAADUeiBjQzZRU+Xfb8Fyqt8Deof2L2u0potytU/njjLi0p2lKtHXexBwAAMA43EwGamcKSigYnaZJkSdgdVvaX9qrWJjPZoWO6t23wMQAAANA4rKgBzdjxvbN066iDo+rzyLfvatVvC2r/OPZV5Zx8ULU2fTqkKSnBFosQAQAA0AAkakAzlpmcoIGdM6Pqk/6jI7R9ZJccZSVF1x8AAADxx6mPAAAAAGAyrKgBQA0WTTpBwWBQFu6qAgAADECiBgA1SE3kn0cAAGAcvokAaBX6te2nnJQctU3kbpYAAMD8SNQAtAozhs8wOgQAAICIkagBQA2e/fgnFbt9SnPadeXxPYwOBwAAtDIkagBQg2c/3qx8l1s56U4SNQAA0ORI1AADlVf49cY33+qHvV9H3Keswid7xnZJ0nZ/G/1v489RHTO/ND+q9gAAAGh6JGqAga6evVRfByfJYvVF1S8pt/LP9X7prk/jEFgLdMPiG7Tbs1ttE9tyvRoAADA9EjXAQGsKfpClQ3RJWqx0TOmoNoltDDl2pBZsWaCZq2eq1Fta4/53znpHKY6UUPm6uY/ok51v1tg2aHVJlqAs/gxdOetLPTvud2H7r5z1pdZsc4XKBcXuGLwCAADQ7H3/lrRkmuQpkSTZ3U3z3Y1EDTCJ7ilHqE/q4IjbZyY51LtDmhryPGa71a5hBw2TzWqLvnMTmrl6pjYXba51f7G7QsFAYuiZZ8UVJQraiuoc0+dLUKG7olp9YWmF8l3Vk7OURHPPEQAAiLMl06RdG0JFiyfYJIclUQNMYniPI3TTEX8yOgxT2beSZrVYlZWUFbZvZ7FHx96/RDmpGVpx53BJUlpCqiz+jNoHDCQquWSM2rVLqLarXUqCctKdYXUpiTZNGnVwI18FAABo1n5bSZPFKqXmKOjwSSqO+2FJ1ACYXlZSlhafuzis7thpi+UKhK+A/fP0WyTd0qBjHHgqJAAAQJjUHGnSOvkKC6W/ZtXfvpGscT8CAAAAACAqrKgBMK3HT35cXr9XDpvD6FAAAACaFIkaANPq366/0SEAAAAYgkQNAAAAAGoz+HrJUywlpjXpYUnUAAAAAKA2QyYYclgSNQCmtfTXpXL73XLanDqh8wlGhwMAANBkSNSARtpeVK69Zd4G9fVbymIcTcty74p7VVBWoOzkbC3uvLj+DgAAAC0EiRrQCM9/sln3vru2QX1tyT8pueusGEcEAACAmPIUS8GgZLE06XVqJGpAI7y/ZnuD+9pT14WVO6V2amw4rcozlx6lCn9ACTYeBwkAAOLoiaOl4jwpLVeatK7+9jFCogY0QiBYtX3B7zrLYrFE3Pd7d6o2/3bG5HE5J+u0HqfFOLqWbcBBGUaHAAAAEDckakCM3Hf2ANmskSdqD36Zpc2/nTX5p8PHy2l3xikyAAAANDecMwQAAAAAJsOKGoBmafG6HXJ7A3I6rBp+SAejwwEAAIgpEjUAzdJf3lqjfJdbOelOEjUAANDicOojAAAAAJgMiRoA00q2JyvFkaJke7LRoQAAADQpTn0EYFpzz55rdAgAAACGYEUNAAAAAEyGFTUAAAAAqM2FsyW/V7I5mvSwJGpALVb9vEc3zfla24vctbbxB4K17tvj3qNrF12rH3b/UHPfoL/RMQIAACDOcg835LAkakAtXvvyF23dUx5R23SnXZYD6pb8ukTfF34fUf+MxIwoo2sdHl75sFwVLqUnpGvSUZOMDgcAAKDJkKgBtfD4AqHtgzukKdFR8yWdCTarxg3pJqs1PFXz+D2h7U6pnZSZmFmtr0UWndj5RHXP6B6boFuYeZvnqaCsQNnJ2SRqAACgVSFRAyLwzKVHqUu7ht8i/vpB1+v0nqfHMCIkJ9qUmmhXcqLN6FAAAEBLtn6+5CuX7EnSwac02WFJ1AA0Sx9OOtHoEAAAQGvw7i1ScZ6UltukiRq35wcAAAAAkyFRAwAAAACTIVEDAAAAAJPhGjUAzdK0eetUVOZVRrJDd445xOhwAAAAYooVNQDN0jur8/Tayl/1zuo8o0MBAACIORI1AAAAADAZTn0EYFrDDhqmIk+RMhIzjA4FAACgSZGoAbV4/7v8GuvXFq7VjK9naK97b539C92FcYiqdfnb4L8ZHQIAAIAhSNSAWlT4A6HtREfVWcJPfvOkPtn2SVRjJdoSYxYXAAAAmlBCipSQVvlnEyJRAyLQId0Z2nZ5XKFtiyyyWCx19h3YfqCGdhoat9jqcv/S1/TaxmcUsLglSdmOflp0ydNhbY594Q8qC9a8eri/0Z0u0UOjrwmV1xVs1fnvXhBRHE+c9C8N694/VJ669FW99cvTdfSo5FCGVl3+Xljd5P9+pyU/FKig2B3RsQHA9D57Qlo+s/52HQdKF80Jr5t9gbT9m/r7Dr5eGjKhquwplp44OrL4Lpwt5R5eVV4/X3r3lrAmdgU1yu2WfeOfJf32czEhRbphZfhYH/xV+u7N+o/ZZ5R0+mPhdf86QSopqL/vyHulw86tKu/6UZp1Rv39JOnqJVJaTlV55QvS0gfr79eup3TZu+F1b14pbfm0/r5HjpNOvCO87uHI7mZsOfOf4RWbP5b+e3VEfTVpXXj5owekVbPq79ftOGnss+F1/z5NKtxUf98TbpeOGl9VLs6Xnj6p/n6SNO4dKat3Vfnb16WFd9ffLzVbumZpeN3cm6QNH9Tfd8BYadTU6p/jJkKiBtRjYOfMWvd9dclXslvN+9fotY3PyG/fESqX+VzV2ngCRQrai+odq7SiLKzsDfgUtNXfT5Iq/L6wcrmvPKK+Xn/1uqLyCuW7qpK0lERbRDEAgGl5iqXiCO5gm9Gpel3Zrsj6eorDy8FgZP0kye8NL/vKq/W1SEqSpP2bJqRVH6t8b2THLd9Tva6kILK+3vCfVwr4In+tgQN+8FSURtbXmV69rqwwsr7u6j+bI47XVxFe9nsi71tTHJH0Lavh0o7SnZH1rSgNLwf8Ubw34d8l5C1r+Gst3xPh53Bvw8aPEfN+wwTQaPtW0oJBi6yBdCU7qv8gSbRmyO8vr3eslITksLLDapfFH9lNPhJs4f/UJNmTIurrUPU2GUkJyvlthTMl0aZJow6OKAYAMK3ENCktt/52yVk110XSN/GApMliiayfJNkc4WV7UrW+QQXldrvldDpl2X9F7UBJmZEdN6lN9brU7MjidYT/vJLVHvlrtR7wy7+ElMj6prSvXpfcLrK+NSV5kcZrT5C03xkmtsTI+9YUR0Sfw3bV61La15xwHujAz4TVFsV7c0Da4kiOrG9Nn5ukNhF+DjMjCi1eLMFgMGhoBM2Uy+VSRkaGioqKlJ5ew1+wKHi9Xs2bN09jxoyRw+GovwMaLZI573ZH5Sl3Aztn6u3rjwvVj3t/nL4q+EqS9PUlX5t6Re2w54cqaCuSxZ+hby+P7rq6eOCzbgzm3RjMuzGazbx7iitXtSyW6klUM9Rs5r2FYd6NUVhYqKysrJjkAXUx7zdMAACAluqJoytPvUrLrX6tEACIB14DAAAAgOmQqAEAAACAyZCoAQAAAIDJcI0a0IINyjxFpd4SpThSjQ4FAAAAUSBRA1qwF8/5q9EhAAAAoAFI1IDflFf49fKKn7W5sLTWNh6/J3RrfgAAACBeSNSA37yx6lfdN6/6LZKtlqrt9ze/34QRAQAAoLXiZiLAb37dU15j/ZhDO4a2t5VsC22nOFJM/bBrAAAANF98ywRq8NAfDlP/3AxlJjuUm5lUY5uHT3i4iaOK3mHPD1XQViSLP0PfXv6J0eEAAAAgQiRqQA26ZaWoX256nW0sstS5HwCAWl04W/J7JZvD6EgAmBSJGgAAQFPLPdzoCACYHNeoAQAAAIDJkKgBAAAAgMlw6iMAAEBTWz9f8pVL9iTp4FOMjgaACZGoAQAANLV3b5GK86S0XBI1ADXi1EcAAAAAMBnTJ2rFxcW6+eab1bVrVyUlJWnIkCH68ssvJUler1d//vOfNWDAAKWkpCg3N1eXXnqp8vLy6hzznnvukcViCfuvb9++TfFyAAAAAKBepj/18corr9SaNWv00ksvKTc3Vy+//LJGjBihtWvXKjU1VV999ZXuuusuDRw4UHv27NFNN92kM844QytXrqxz3P79+2vRokWhst1u+qloddbmubT6172NHicYDOrnsm+1x1uVwAcCAeXt3KZli/JktVb+vmJNfpEcmSWSpI/ydmpLRUr1mArXNjoeAAAAoD6mzk7Ky8v15ptv6u2339awYcMkVa6GzZ07V08++aSmTp2qhQsXhvV54okndPTRR+uXX35Rly5dah3bbrcrJycnrvGj4TYWFGvM4x/HZCx7+moldZpTfYdDWlOwX9kmOTtWbr74o6QfY3J4Q00ceI/K/RVKsiUYHQoAAACiYOpEzefzye/3y+l0htUnJSXpk08+qbFPUVGRLBaLMjMz6xz7xx9/VG5urpxOpwYPHqz777+/zsTO4/HI4/GEyi6XS1Ll6ZderzfCV1Szff0bO05Lsvrn3TEby+bcGrOx9rFb7eqR1sP079nFh50Q2jZDrHzWjcG8G4N5N0ZzmXe7grJICioon8ljjURzmfeWhnk3RlPNtyUYDAab5EgNNGTIECUkJGj27Nnq0KGDXn31VY0bN069evXS+vXrw9q63W4dd9xx6tu3r1555ZVax3z//fdVUlKigw8+WNu3b9eUKVO0bds2rVmzRmlpaTX2ueeeezRlypRq9bNnz1ZycnLjXiSq+XKnRS9vtEmSjswKqE9Gwz+m39vmabPtU0lSL/8JSgm2q7N9h6SgUur5FUZ3e3e1tbVtcEwAgNZt1JqblOTdo3JHG31w6GNGhwMgCmVlZbroootUVFSk9PT0uB3H9Inapk2bdPnll2vZsmWy2Ww64ogj1KdPH61atUrr1q0LtfN6vRo7dqy2bt2qjz76KKpJ27t3r7p27arp06friiuuqLFNTStqnTt31q5duxr9Bnm9Xi1cuFAjR46Uw+Fo1Fgtxdur83Trm2skSX87ra/+eEztq531eXjVw3plfWXi/sLIFzSw/UDm3CDMuzGYd2Mw78ZoLvNuf3yALMXbFUzrKN+N3xkdTqM1l3lvaZh3YxQWFqpjx45xT9RMfeqjJPXs2VNLly5VaWmpXC6XOnbsqPPPP189evQItfF6vTrvvPP0888/68MPP4x6wjIzM9WnTx9t3Lix1jaJiYlKTEysVu9wOGL2FyOWYzV3Nrutattma9S8WG1VNze12+1hY7X0Of/3qkWha9QuO3KE0eGEtPR5Nyvm3RjMuzHMP++W3/5vMXmc0TH/vLdMzHvTaqq5Nn2itk9KSopSUlK0Z88eLViwQA8++KCkqiTtxx9/1JIlS9SuXd2ntdWkpKREmzZt0iWXXBLrsAFDTf/mHgVtRbL4M0yVqAFAq5eQIiWkVf4JADUwfaK2YMECBYNBHXzwwdq4caNuu+029e3bV+PHj5fX69Uf/vAHffXVV3r33Xfl9/uVn58vSWrbtq0SEirvdDd8+HCdffbZmjBhgiTp1ltv1emnn66uXbsqLy9Pf/vb32Sz2XThhRca9joBAEArckPdjxECANMnakVFRZo8ebK2bt2qtm3bauzYsbrvvvvkcDi0ZcsWvfPOO5KkQYMGhfVbsmSJTjzxREmV17nt2rUrtG/r1q268MILVVhYqPbt22vo0KFasWKF2rdv31QvCwAAAABqZfpE7bzzztN5551X475u3bopknuhbNmyJaw8Z04Nz9QCAAAAAJOw1t8EAAAAANCUTL+iBgAA0OJ88FepfK+UlCmNmmp0NABMiEQNpuD2+rVhR3Go/EtheVT9C8sLlV+aX+O+XeW7aqwHAMAw370pFedJabkkagBqRKIGw5V4fDrpHx9pZ7Gn/sY1WJ63XNctuk6+oC/GkQEAAADG4Bo1GO7rX/bUmaR1aZtcZ/9lW5dFlKTZLDblpuZGHR8AAADQ1FhRg+H2v3HnwIMyNKhzZqjcv1OGhvWu+7EJQVUNMKrrKLVLqv7Qc4ssOv6g45WdnN3oeN/7drumL1yvUo+/3rbvTDhO2enOUHn257/o8cU/yudcrYr0eZK15gQ12ZKjFePfCKsb8dLVKvCurfeYgzJP0Yvn/LXedgDQ6n3/lrRkmuQpqXn/uHekrN5V5W9flxbeXf+4qdnSNUvD6+beJG34oKpcUvPp+gCwD4kaTOWEg7M1cWSfBve/rP9lGtB+QAwjqm76wvXatLM0orb+Ax4fUVbhU77LreSs92Rz7Ky1n8eXVK2uzOdS0FZU7zFLvVVfOL69/JOI4gSAVmnJNGnXhtr3Bw44W8NbVnldWUOU76m5b2Jqw8YD0OKRqAFRevrSo/RzYamuffkrtUlOqLOtzWIJKycn2JWT7lSZvaJyHTBokSWQXq1fojWjWl2yPV0l3ur1B0px8EMfACKybyXNYpVSc6rvtx7wNcmRXHnzj/qk1nD2RlKb6n0TU6WT/hJZrABaHRI1IEo926eqZ/tUrZ/6+6j7XnRMF110TBcNf32aCsqk7JT2Wnzu4oj6Lrrk6aiPBwCIQGqONGld/e0OO7fyv4Y4/bGG9QPQapGoAQb408A/qcxbpmRH3TdKAQAAQOtEogYY4Nw+DfyNLAAgdq5eIgX8ktVmdCQAUA2JGhClt1dvU3mFX0kJNp05qJPR4QAAGiqthuvSAMAkSNSAKN0/7wflu9zKSXeSqAEAACAuSNQAA+ws2yl/0C+bxab2yXU/Jw4AAACtD4kaDBc44Flj0fUNKNiI/ka54L0LVFBWoOzk7Ijv+ggAiLGVL0gVpVJCinTUeKOjAYAwJGow1F//951eXvFLg/o++c2TevbbZ1URqIhxVACAVmHpg5UPoU7LJVEDYDpWowNA61VU5q2WpLVNdkTc/4U1L1RL0jITM2MRGgAAAGAoVtRgmAp/IKx8/lGddfbhB0Xc3+v3SpKS7Enq27avTu58sjqnd45pjAAAAIARIkrUjjjiiKgGtVgseuedd9SpE3fEQ2RG9uug//vDYQ3q2z2ju178/YsxjggAAAAwTkSJ2urVqzVp0iSlpqbW2zYYDOqBBx6Qx+NpdHAAAAAA0BpFfOrjbbfdpuzs7IjaPvzwww0OCAAAAABau4gStc2bN6t9+8if9bR27Vrl5uY2OCjAzNqnJYb9CQAAAMRaRIla165doxq0c2du6ICWa+4NQ40OAQAAAC1cg+/66PP59K9//UsfffSR/H6/jjvuOF1//fVyOp2xjA8AAAAAWp0GJ2o33nijNmzYoHPOOUder1cvvviiVq5cqVdffTWW8QEt0rOjnpU/4JfNajM6FABovdr1lJzpUkrkl3cAQFOJOFF76623dPbZZ4fKH3zwgdavXy+brfKL5ujRo3XsscfGPkKgBeqe0d3oEAAAl71rdAQAUKuIE7Xnn39es2bN0j//+U/l5ubqiCOO0J/+9CeNHTtWXq9XzzzzjH73u9/FM1bAFCb/9zsVlVcoIylB958zwOhwAAAA0AJFnKjNnTtXr732mk488UTdcMMNevrpp/X3v/9df/nLX0LXqN1zzz1xDBUtSXmFX7e/8U3E7fNL8/XAFw9oa/HWUJ0v6ItHaPVa8kOB8l1u5aRzPSYAAADiI6pr1M4//3yNHj1at99+u0aPHq2nnnqKZ6ahQRau26El63eGyk5H3ddq/Wf9f7T4l8U17nPaml/C9N5P78ntc8tpd+rUHqcaHQ4AAABMJuqbiWRmZurpp5/WsmXLdOmll+qUU07R3//+d+72iKgUlXvDypccW/cjIFwVrrByoq3yGWYZCRm6tN+lsQ2uCUxfNV0FZQXKTs4mUQMAo7x5pVRWKCW3k8Y+a3Q0ABDGGmnDX375Reedd54GDBigiy++WL1799aqVauUnJysgQMH6v33349nnGjBHj53oI7u3jbi9q+d9ppW/nGlVv5xpRaft1jDuw6PY3QAgBZry6fSpg8r/wQAk4k4Ubv00ktltVr10EMPKTs7W9dcc40SEhI0ZcoU/e9//9P999+v8847L56xAgAAAECrEPGpjytXrtQ333yjnj17avTo0erever24occcoiWLVump59+Oi5BAgAAAEBrEnGiduSRR+ruu+/WuHHjtGjRIg0YUP225FdffXVMgwMAAACA1ijiUx9ffPFFeTwe3XLLLdq2bZv+9a9/xTMuAAAAAGi1Il5R69q1q9544414xgIAAAAAUISJmsvlUnp6esSDFhcXKy0trcFBAWZ2xqBcFZV5lZHsMDoUAAAAtFARJWpt2rTR9u3blZ2dHdGgnTp10urVq9WjR49GBQeY0Z1jDjE6BAAAALRwESVqwWBQzz77rFJTUyMa1Ov11t8IaMWykrLC/gQAAAD2F1Gi1qVLFz3zzDMRD5qTkyOHg9PCWqsNO4o1+/NfVOrx1dpm486SiMYq9ZbqlXWv6PPtn8cqPFN47bTXjA4BAHDkOMntkpyRX94BAE0lokRty5YtcQ4DLcltb3yrb37dG3F7ax33Hn1jwxua8fWM8PaWiG9WCgBA7U68w+gIAKBWEd/1EYjUtj3lEbdtm5Kgob3a17p/e+n2sHLvNr3VO7N3g2OLhZMf/kgFLo+y0xP14aQTDY0FAAAALROJWit08sMfqczjr7fdfWcfquGHdAiVv9tapKteXFlvv92lntD2oonDJEl///gpfbX37WptfRZp+OtV5Qxbd3087qWaBw4ka+OuAh3+7xNq3D20/Vj98/RbQuUdJUUa+Z9Ta40zGAzqrpceqozv2Id1Zr9jQvse/+xtPfvDQzX282cEpQxpl9Wi099qo7lnzw3b//DKhzVv87xajytJmYmZevzkx9UptVOd7QDEmadYeuLoyNpeOFvKPbyqvH6+9O4ttTa3K6hRbrfsv9wr3bAqfOcHf5W+e7P+Y/YZJZ3+WHjdv06QSgrq7zvyXumwc6vKu36UZp1Rfz9JunqJlJZTVV75grT0wfr7tespXfZueN2bV0pbPq2/75Hjqq9wPRzhzZvOeVrqfnxVGMXrZH/8z5Is9fedtC6yYwBAEyNRa4UKXB6V1HH92D5ubyCsXOEPKN/lrv8AVo9kCapTZpJ6ZVc+piEgt2QvqtY0eEC53F+9TdW4ZdXa76+4Ivy6t2AwoKCtjvH2O77bVxFWX+p119rXaqvqu7O8+jy6KlwqKKv7S1SaI00Pr3xYnVI7adJRk+psCyCOgkGpOC+ytv4DbpTlK6+zr0VSkqRgcQ032CrfG9lxy/dUryspiKyvtyy8HPBF/loDB/wyr6I0sr41XetVVhhZX7erel3E740nrGgNemUp3l5LYwBoHkjUWqHs9ESleup/652O8GvBEmxW5aQ76+1XnD1NVodLxf4MSWMkSWkJqbL4M+rtm2Sro40/VRbZat2dlhB+V1KLxVrnMYPBoCyWyt+2Ou0JYftSHM46+1pkUarTrrZJ1e+Emp6Qruzkuh9lUewt1sa9G3VKt1PqbAcgziwWKS03sra2A26SZU+qs29QQbndbjnT2lXfmZQZ2XGT2lSvS43sUTlyJIeXrfbIX6v1gH9rE1Ii65tSw6nsye0i61tTkhfxe5MYVgxYHAqmdZQlkhU1ADApSzAYrGuRArVwuVzKyMhQUVFRVA8Dr4nX69W8efM0ZsyYFnG3zAHPDZXsRbL4M/Tt5Z80aqwHvnhAr6x7RZL0yphXdFj7w2IRYoub8+aCeTcG824M5t0YzLsxmHdjMO/GKCwsVFZWVkzygLpEffu8+fPn65NPqr58z5w5U4MGDdJFF12kPXtqOEUDAACz+ewJacn9lX8CAGBCUSdqt912m1yuyvPIv/vuO02aNEljxozR5s2bNXHixJgHiNiZNm+d/vzGt5o2jwunAbRyy2dKSx+o/BMAABOK+hq1zZs3q1+/fpKkN998U6eddpqmTZumr776SmPGjIl5gIidd1bnKd/lVk66U3eOifBOWgAAAACaXNQragkJCSorq7yT1KJFizRq1ChJUtu2bUMrbQAAAACAhot6RW3o0KGaOHGijjvuOH3xxRd67bXXJEkbNmzQQQcdFPMAAQAAAKC1iTpRe+KJJ3TdddfpjTfe0JNPPqlOnSof2Pv+++/rlFO41XhrtL2oXIvXFcgfqLyBaFARPWI0TGF5oZb8ukQV/vDnma3fvT42QQIAAADNSNSJWpcuXfTuu+9Wq3/kkUdiEhCaF58/oLNnfhb2IOyUXsGoErVgMKhrFl6j9XtIygAAAACpAdeoSdKmTZv017/+VRdeeKEKCgokVa6off/99zENDua3u7QiLEnbX4It8o9XfUlaqiNVPTN7RhUbAAAA0FxFvaK2dOlS/f73v9dxxx2nZcuW6b777lN2dra++eYbPffcc3rjjTfiESeagQGdMnTF0O7aVnafEh1BHdU1K+oxuqR10bWDrg2rs8iio3OOVoojJVahAgAAAKYWdaJ2xx13aOrUqZo4caLS0tJC9SeffLKeeIIHh7ZmHTOcOuvwTpI6NXiMNs42Oq3HabELCgAAAGiGok7UvvvuO82ePbtafXZ2tnbt2hWToAAAiKuOA6WMTlJy9Cv/AAA0hagTtczMTG3fvl3du3cPq//6669Dd4CEOZ3UN1tF5RXKSEowOhQAMNZFc4yOAACAOkWdqF1wwQX685//rNdff10Wi0WBQECffvqpbr31Vl166aXxiBExcv85A5rkOEt/XSq33y2nzakTOp/QJMcEAAAAWpKoE7Vp06bp+uuvV+fOneX3+9WvXz/5/X5ddNFF+utf/xqPGNHM3LviXhWUFSg7OVuLOy82OhwAAACg2Yk6UUtISNAzzzyju+66S2vWrFFJSYkOP/xw9e7dOx7xAQAAAECrE3Wi9sknn2jo0KHq0qWLunTpEo+YAACIr9kXSGW7Km8mwvVqAAATijpRO/nkk9WpUyddeOGF+uMf/6h+/frFIy7EwekzPtHOYo/apyVq7g1DjQ4HAIyz/RupOE9KyzU6EgAAahR1opaXl6c5c+bo1Vdf1QMPPKDDDjtMF198sS688EIddNBB8YgRMbKz2KN8lzumY/6yu6zO/QVlBcoryauzTVDBWIYEAAAANHtRJ2pZWVmaMGGCJkyYoM2bN2v27NmaNWuWJk+erGHDhunDDz+MR5wwode+/EV/fvO7WvdX+Cs06o1R8gf9TRgVAAAA0PxZG9O5e/fuuuOOO/TAAw9owIABWrp0aaziQjPw4Q8FYeXuWSlh5Qp/RdRJWtf0ro2OCwAAAGjuol5R2+fTTz/VK6+8ojfeeENut1tnnnmm7r///ljGBpML7nfG4tXDeui6k3rV2vaUbqcoOzm7zvHaONvo7F5nxyo8AAAAoNmKOlGbPHmy5syZo7y8PI0cOVKPPfaYzjzzTCUnJ8cjPjQTVx7fXRlJjlr3X3zIxRqUPajpAgIAAACasagTtWXLlum2227Teeedp6ysrHjEhGYu2Z6sFEeKbBab0aEAAAAAzVLUidqnn34ajzjQgsw9e64k6aEvH9KLa180OBoAAACg+YkoUXvnnXf0+9//Xg6HQ++8806dbc8444yYBAYAAAAArVVEidpZZ52l/Px8ZWdn66yzzqq1ncVikd/PrdgBACY3+HrJUywlphkdCQAANYooUQsEAjVuo3mZPKavyiv8Skrg2jEArdyQCUZHAABAnaK+Ru3FF1/U+eefr8TExLD6iooKzZkzR5deemnMgkNsnTmoU5Mc5+GVD8tV4dIPu39okuMBAAAALU3UD7weP368ioqKqtUXFxdr/PjxMQkKzdu8zfP03x//qy1FW4wOBQAAAGiWol5RCwaDslgs1eq3bt2qjIyMmAQF8wkGg/L4wk97Dez/xGsAaE48xVIwKFksXKcGAPHgdRsdQfz4mua1RZyoHX744bJYLLJYLBo+fLjs9qqufr9fmzdv1imnnBKXIBEbm3aWyB8Iyma1qGf71Ij7lXp8Ov/p5VqzzRXV8cp8ZdGGCABN44mjpeI8KS1XmrTO6GgAoOXweaR/nypt/dLoSOLG4WmaxYqIE7V9d3tcvXq1Ro8erdTUqi/6CQkJ6tatm8aOHRvzABE7Fz/zufJdbuWkO7XizuER9/v4x111JmmJdqtSEqp/lCyyKKjKD3IbZ5voAwYAAEDz8vOnLTpJa0oRJ2p/+9vfJEndunXT+eefL6fTGbegYC5ef9Upj13bJatjRtV7b7da9YcjD1JKYg2JmsWi4G+nR3ZN7xr/QAEAAGAsv7dqO7OLlNnyvgMGyjySFsX9OFFfozZu3Lh4xIEYKnC5dcYTn1avL47+fNoFWxbokXWPKaVX5Q1kKpwO7Uy0KSspS6+d9lpY2ynLp2jZ1mXaVb4rrD47KTvq4wJx8/1b0pJpkqdEOnKcdOId4fsfPiSycc55Wup+fFV588fSf6+OrO+Bp9p99IC0alb9/bodJ419Nrzu36dJhZvq7GZXUF0zT5E0pqqyOF96+qTI4h33jpTVu6r87evSwrvr75eaLV2zNLxu7k3Shg/q7ztgrDRqanjdjKOkitL6+572iHTwfqfi530tvXpReJuS/PrHAQA0zuGXSifcZnQUMecvLJSuz4r7cSJK1Nq2basNGzYoKytLbdq0qfFmIvvs3r07ZsGhfrM//0VlFT4lJ9h10TFdJEn+YFD5rtqTspTEyJ+jNnP1TO30/Cqro7Jc4pdKarn0rMhTpIKyglDZoto/J4BhlkyTdm2o3HbXcEpvcV5k4/g91cuR9j2Q2xVZ37LC6nWlO+vta5FkTz/g34SAP/J4A77wsres4a+1fE9kfcv3Vq8rzpcqiuvv6ysPL/u9tR8zMfLrdQEAaEoRJWqPPPKI0tLSQtt1JWpoWo8v/jF03dm+RM1msSgnveZTU1MSbZo06uCIxy/1Vv72Ohi0KOhLU7rToeTfVtQOlJGYoezkytWzFEeK9rj3aK9nb5SvCIgzT0nlnxar5Eyvvj8tN7JxbInVy5H2PZAzPbK+ye2q16W0rznh3E9QQfmsB/ybYLVFHq/1gB8VjuTI+qbWsJqe1CayvkmZ1evScqSKCO7QaE8KL9scNR8zMVU66S/1jwcAgAEiStT2P93xsssui1csiJHsKG8WEomgL02lG+/UxNP66Yqh3Wts87fBfwsrj3xjpOSpsSlgvNSc6qc9Sg2/A2D34xve98Q7ao4lEpe9W28Tn9ern+fNU//9K9NyGh7vYedW/tcQpz/WsH6SdMPKhvXLPZw7OwIAmp2oH3j91Vdf6bvvvguV3377bZ111lm68847VVFREdPgpMoHad98883q2rWrkpKSNGTIEH35ZdWdZILBoO6++2517NhRSUlJGjFihH788cd6x505c6a6desmp9OpY445Rl988UXMYwcAAACAhog6Ubvmmmu0YUPl9R0//fSTzj//fCUnJ+v111/X7bffHvMAr7zySi1cuFAvvfSSvvvuO40aNUojRozQtm3bJEkPPvigHn/8cT311FP6/PPPlZKSotGjR8vtrv0arddee00TJ07U3/72N3311VcaOHCgRo8erYKCglr7AAAAAEBTiTpR27BhgwYNGiRJev3113XCCSdo9uzZ+ve//60333wzpsGVl5frzTff1IMPPqhhw4apV69euueee9SrVy89+eSTCgaDevTRR/XXv/5VZ555pg477DC9+OKLysvL0//+979ax50+fbquuuoqjR8/Xv369dNTTz2l5ORkPf/88zGNvyWYeOREnd35ZnkKxtTfGAAAAEBMRH17/mAwqECg8rlaixYt0mmnnSZJ6ty5s3bt2lVX16j5fD75/f5qz2xLSkrSJ598os2bNys/P18jRowI7cvIyNAxxxyj5cuX64ILLqg2ZkVFhVatWqXJkyeH6qxWq0aMGKHly5fXGovH45HHU3XBlctVefG+1+uV1+utrVtE9vVvyDj7HigdVLDRcdRkVOdR8u7N14uubyVJfr8/8uMEq2KMR2yN0Zg5R8OZYd7tCsqi326w0UrefzPMe2vEvBuDeTcG824MM867xecLJRj+gF8BE8UWK00131EnakcddZSmTp2qESNGaOnSpXryySclSZs3b1aHDh1iGlxaWpoGDx6sv//97zrkkEPUoUMHvfrqq1q+fLl69eql/PzK5+AceNwOHTqE9h1o165d8vv9Nfb54Ycfao3l/vvv15QpU6rVf/DBB0pOTo72pdVo4cKFUfdxu22SLHK73Zo3b15M4jjQ17sskipv6b9u3VrN2/t9RP3Ky8t/izF+sTVWQ+YcjWfkvI9yu5Wkys/lByb9XMYLn3djMO/GYN6Nwbwbw0zz3qFotY79bXvDhg3a4Gp5P2vLymp5VlWMRZ2oPfroo7r44ov1v//9T3/5y1/Uq1cvSdIbb7yhIUOGxDzAl156SZdffrk6deokm82mI444QhdeeKFWrVoV82PVZfLkyZo4cWKo7HK51LlzZ40aNUrp6TXc4jsKXq9XCxcu1MiRI+VwOKLqO+37pSqq8MjpdGrMmBMaFUdt9n7xq/Rj5R3TDjmkn8YMqfkJ89tKtumBLx9QXmnl84pKVHkb9MrYzHXqZGPmHA1nhnm3VbytQPluJSa1Nd3nMl7MMO+tEfNuDObdGI2e990/ybZgsiyuX2MfXAsWDAZVWlqqlJQU8zw+a99jcCT16dNHvYa2vJ+1hYU1PNc0DqJO1A477LCwuz7u89BDD8lmi/xBypHq2bOnli5dqtLSUrlcLnXs2FHnn3++evTooZycHEnSjh071LFjx1CfHTt2hK6jO1BWVpZsNpt27NgRVr9jx47QeDVJTExUYmJitXqHwxGzHwQNGWvfQ6UtssTlB9Lmos1au3ujLAk7FaxoL7cvWOtx/rvpv/p0+6fV6pPsSab9YRnL9w+RM3Tez626FjXqi3SbOT7vxmDejcG8G6PB8/71v6WfFsc8npbOIilNkmq/h56hbImpsrXAv4dN9W9L1InaPqtWrdK6dZWrLP369dMRRxwRs6BqkpKSopSUFO3Zs0cLFizQgw8+qO7duysnJ0eLFy8OJWYul0uff/65rr322hrHSUhI0JFHHqnFixfrrLPOkiQFAgEtXrxYEyZMiOtriIfuWSlKc9qVlVo9iYyFKz+4UgVlBUrukq7SjXcqO6324xR7i0PbSfYk2Sw2JTuSdfVhV8clNgAA0EK4XeHlxMadrdRaVF5v7ZPdYQ/98t402veVDh1rdBTNWtSJWkFBgc4//3wtXbpUmZmZkqS9e/fqpJNO0pw5c9S+ffuYBrhgwQIFg0EdfPDB2rhxo2677Tb17dtX48ePl8Vi0c0336ypU6eqd+/e6t69u+666y7l5uaGkjBJGj58uM4+++xQIjZx4kSNGzdORx11lI4++mg9+uijKi0t1fjx42Mae1N49epj628UQ21SEiJq99LvX9LBbQ+OczQAAKDFuf4LqT3fISLh83o1b948jRkzhhXkFijqRO2GG25QSUmJvv/+ex1yyCGSpLVr12rcuHG68cYb9eqrr8Y0wKKiIk2ePFlbt25V27ZtNXbsWN13332hD+Ptt9+u0tJSXX311dq7d6+GDh2q+fPnh90pctOmTWF3pDz//PO1c+dO3X333crPz9egQYM0f/78mN8MBQAAAAAaIupEbf78+Vq0aFEoSZMqT32cOXOmRo0aFdPgJOm8887TeeedV+t+i8Wie++9V/fee2+tbbZs2VKtbsKECc3yVEcAjfTv06TSnVJKe+myd42OBgAAoEZRJ2qBQKDGpVWHwxF6vhoAmFbhJqk4r/r1EAAAACYS9U3PTj75ZN10003Ky8sL1W3btk233HKLhg8fHtPgUL+b5nytS577XDfN+droUAAAAADESNQrak888YTOOOMMdevWTZ07d5Yk/frrrzr00EP18ssvxzxA1O3zn3Yr3+VWTrqz/sYAAAAAmoWoE7XOnTvrq6++0qJFi/TDDz9Ikg455BCNGDEi5sEBAAAAQGvUoOeoWSwWjRw5UiNHjox1PAAAAADQ6kV9jZokLV68WKeddpp69uypnj176rTTTtOiRYtiHRsAAAAAtEpRr6j985//1E033aQ//OEPuummmyRJK1as0JgxY/TII4/o+uuvj3mQiK8f8l16afnPKvX45Ar8pG3+JQrIK0kKBrvIWdFRxW6fnLlzNPunhVqyu+br4b7b+V1Thg0AQOv06xfSVy9KPo/RkYTYggEdsS1PtrffkSwNWAfY+kXsgwKauagTtWnTpumRRx4JewbZjTfeqOOOO07Tpk0jUWuG7vzvd/rql72SpOQeM2VL3BneIEFyJFRufrVb0u76x7RZbDGNEQAA/Ob18ZJrq9FRhLFK6ixJe2IwGN8hAEkNOPVx7969OuWUU6rVjxo1SkVFRTEJCk1re5E7tG117G30eIe2O1Q9Mns0ehwAAFADkyVpMXXQ0VK7nkZHAZhC1CtqZ5xxht566y3ddtttYfVvv/22TjvttJgFhqaXlZooOWzy+L1KtDn1xLDwxy10SHfKbq07t7dYLOqU2kkWiyWeoQINd8LtUkWplJBidCQA0DjJ7aQrzXGPAK/Pp48++kgnnniiHPYG3auu8pTJzK4S3yEASQ1I1Pr166f77rtPH330kQYPHiyp8hq1Tz/9VJMmTdLjjz8eanvjjTfGLlLEnd1qUeC3fxy7pHfWsV0O1usbXleZt0zJjmQd2+VcgyMEYuCo8UZHAACx0aa71NYkZ7B4vSpLXFcZk8NhdDRAixB1ovbcc8+pTZs2Wrt2rdauXRuqz8zM1HPPPRcqWywWErUmcMHRnVXs9inN2cDfXtXjqW+eUkFZgbKTs3VuHxI1AAAAoClE/e1+8+bN8YgDDXTziD5GhwAAAAAgxuKzDAMAZlWcLwX8ktUmpeUYHQ0AAECNSNQAtC5PnyQV50lpudKkdUZHAwAAUKMGPJEQAAAAABBPrKg1c8dOW6x8l1s56U6tuHO40eEAAAAAiAFW1AAAAADAZBq0ovbxxx/rX//6lzZt2qQ33nhDnTp10ksvvaTu3btr6NChsY4RMfTllt365te9YXUlHp+siXnypv6sQMBrTGAAALRWgYC0cZG0a4PRkQAwkagTtTfffFOXXHKJLr74Yn399dfyeDySpKKiIk2bNk3z5s2LeZCIje+2Funcp5ZXq7fYipXSe6YqLH4pYEBgAAC0Zmv/J70x3ugoAJhM1Kc+Tp06VU899ZSeeeYZOfZ78vxxxx2nr776KqbBIbbW5btqrLcmFshi8YfVHZF9hCSpW3o39czoqW7p3eIdHgAArdOO7xvWr+vg2MYBwFSiXlFbv369hg0bVq0+IyNDe/fujUVMaAIXHt1ZQ3u1lyRtKrbpmY2V9Sd3PlkX9L1AR+ccLUl6bvRzRoUIAEDrM+x2qUO/+tsltZW6HR//eAAYJupELScnRxs3blS3bt3C6j/55BP16NEjVnGhHss3FeqW11aroNjdoP4DOmXq1MM6SpJmfv3fUP2K7Su0pnCNJOmoDkfp/4b9X+ODBZrC929JS6ZJnpLw+pH3SoedW1Uu3920cQFANLodJ/U40egoAJhA1Kc+XnXVVbrpppv0+eefy2KxKC8vT6+88opuvfVWXXvttfGIETWo8AeU73IrEKwspyTaGjzW25veDm2X+cpUUFaggrIC7fXsbWSUQBNaMq3yQvzivPD/vGXh7c57sfLPxNSmjxEAACBCUa+o3XHHHQoEAho+fLjKyso0bNgwJSYm6tZbb9UNN9wQjxhRgwSbVTnpTkmVSdqkUQc3eCy3r2pVLsWeopSEFElSZmJmo2IEmtS+lTSLVUrNqap3JIe3a9tDyuojnfSXposNAAAgSlEnahaLRX/5y1902223aePGjSopKVG/fv2Umspvp5vS4J7t4vKA64sOuUg3HnFjzMcFmkxqjjRpXe37s3pLE75sungAAAAaoEHPUZOkhIQE9esXwcWuML2ggkaHAAAAAGA/USdqJ510kiwWS637P/zww0YFhPot31SoCn9ACTarBvdsZ3Q4AAAAAGIs6kRt0KBBYWWv16vVq1drzZo1GjduXKziQh1ueW218l1u5aQ7Y3L64/Gdjtfcn+bGIDLAQKnZ4X8CAAA0Y1Enao888kiN9ffcc49KSkpq3AdzO73n6aFEra7VUsDUrllqdAQAAAAx0+Br1A70xz/+UUcffbT+8Y9/xGpIxJg/wLVoAIAWyFsubVslBQOy+HzKKl4ry5Y0yR6zrznxtfcXoyMAYEIx+xds+fLlcjqdsRoOcTD5v9/VWL//zUQsYkUNANCM+H3SzGOkvT9Lqvxic5wkbTQyKABovKgTtXPOOSesHAwGtX37dq1cuVJ33XVXzAJDbPn8gbByj/YpBkUCAEAMFf4YStKaP0vlsx4BQA1I1DIyMsLKVqtVBx98sO69916NGjUqZoEhvo7p3ja0/edlfw5tc40amq25N0nle6SkNtLpjxkdDQAjdDhU/p7DtWnTJvXs2VM2q9XoiKLT4yQps4vRUQAwiagSNb/fr/Hjx2vAgAFq06ZNvGJCnP2uWxsSMrQ8Gz6QivOktFyjIwFglNzDFTjpLq0rn6fuJ42RzeEwOiIAaLCoftVks9k0atQo7d27N07hAAAAAACiPifg0EMP1U8//RSPWGAC3EwEAAAAMF7UidrUqVN166236t1339X27dvlcrnC/gMAAAAANE7E16jde++9mjRpksaMGSNJOuOMM8KucwoGg7JYLPL7/bGPEmFW3Dk8bmOzogYAAAAYL+JEbcqUKfrTn/6kJUuWxDMeAAAAAGj1Ik7UgsHKhyKfcMIJcQsGJsCCGgAAAGC4qK5R45buAAAAABB/UT1HrU+fPvUma7t3725UQKjfo4s2qNjtU5rTrptH9DE6HAAAaucpkYJxvH7dUxK/sQHAQFElalOmTFFGRka8YkGE5nzxq/JdbuWkOyNO1Oatya+x/sc9P2qvZ2+ozM1E0GwNGCuV75WSMo2OBMA+b1wurXnT6CgAoFmKKlG74IILlJ2dHa9YEEevr/w1tJ2R5AhtL9iyIKxdu6R2TRYTEFOjphodAYD9Fe9o+iQtle8oAFqOiBM1rk9r3vyBYGj7puFVq3C+gC+0fUjbQzSm+5gmjQsA0EIFvFXbKe2lnAHxPV5mF+noa+J7DABoQlHf9RHNX6/s1Brrb/vdbUpxpDRxNACAFq/rcdJ5s5rmWF5v/W0AoBmI+K6PgUCA0x5buB92/2B0CAAAAAAU5e350bI98+0zRocANNyMo6RpB1X+CQAA0MyRqAFoGSpKpYriyj8BAACaORI1AAAAADAZEjUAAAAAMJmonqMGczimR1vtLq1Q25QEo0MBAAAAEAckas3QYxccbnQIAAAAAOKIUx8BAAAAwGRYUWuBnvjwR7351Tb5A1UPKd/hctfYdu5Pc5sqLABoOFee9M4NUuFGoyOJmD0ojSgrk33z3ZLF6GgMEPAbHQEANGskai1MYYlHDy/coGCw5v0JNqts1qpvDAVlBaFti6U1fpMA0CysfkXauMjoKKJikZQiSRUGB2IGCalGRwAAzQ6JWjN04dMrtKvEo6zURL169bFh+8oq/KEkLcFmVZqz6i122Kwaf1w3Jdirznh12pxy+ytX2+xWPg4ATMpTXLWdmCHZHMbFEqGgpIoKjxISElvlglpIekfp6CuNjgIAmh2+mTcz7327Xct/KpQ97VvtSF+kKxZ003Ojnwtr48ydI1vyT3I6bMpMDv8y858C6T+vV27/ofcfQvV92vTRm2e8Gff4W4xvX5cW3l1/u9Rs6Zql4XVzb5I2fFB/3wFjpVFTw+tmHBXZA51Pe0Q6+JSqct7X0qsX1d9PkiZ8ISWmVZU/e0JaPrP+fh0HShfNCa+bfYG0/ZtQ0a6gRrndsm/8s8LOBRt8vTRkQlXZUyw9cXRk8V44W8o9vPI1+8ole1Jk/dB8Xfiq1O04o6Ool8/r1fx58zRmzBg5HOZPLAEA5kKi1sxMX7hekpTQfqGCjp36bldxtTYWW6msDpcqJBWU1T5Wsbd6X0TIWyYV5zWsb/meyPqW761eV5wvVUTwvvnKw8t+b+TxHnjerKc4sr4ZnarXle0K62uRlCRJ3gPaeQ54TcFg5PH6fxts/8QUAACgmSNRa2ZKPZUXZ1usHklS+YFfyCUF/SkKeNNrXFHbX5ojrdZ9qIcjWUrLrb9danb1uqQ2kfVNyqxel5YjVUTwvh24qmRzRHZMSTrwWsXEtMj6JmfVXLdf36CCcrvdcjqdsuy/opZ4wGuyWCKPtxmcAgcAABAtErVmyma1KCgpO7l6IuDOu0CSdPLAXM04t+5nrj2/5vl4hNfyHXZu5X8NcfpjDT/uDSsb1i/3cGnSuob1HTIh/LTEaBxwKqTP69UHkZwKlpjW8HgBAABaABI1IBq7fpQCPslql7J6Gx0NAAAAWigSNSAas86ovHYqLZcVHwAAAMSNtf4mAAAAAICmRKIGAAAAACbDqY/NzI3De6uswqfnf7Gr2Gd0NAAAAADigUStmbnomC6SpFdft6nYJ7nKfbrulVWh/WUV/ojH+jL/S7n97pjHCAC18lVInz0m5X8XXb8d38cnHgAATIpErZn608A/6bWVG/XNL+Watze/xjZ2q6XGekkKBoO6fdntobLNYot5jABQzYb50odTGzeGlR9dAICWj2vUmqlz+5yrpPKT5d17TI37kxNsOmNQ7Q8MDgQD2lW+K1Q+s9eZMY8RAKop3t64/h0GSJ2OiE0sAACYGL+WbGYKXG75g0HZLOGrZR/cMkxpzqq3MyPJoeSEyN7eXpm9dPEhF8c0TgCo1+8flPqeFnl7i0VK61j5JwAALRyJWjNzxhOfKt/lVk66U707pIbqczKcSnc6GjRmWkJarMIDgMgltZUyOhkdBQAApsSpj81UwFqkCu2Wxe4yOhQAAAAAMcaKWjPlzp6utbYiJXdLV+nGO40Op/W4eokU8EtWbr4CAACA+CFRA6KRlmN0BAAAAGgFOPURAAAAAEyGRA0AAAAATIZTH4ForHxBqiiVElKko8YbHQ0AAABaKBI1IBpLH5SK86S0XBI1AAAAxA2JWiu1tnCt0SEAaC0CAenHD6SC76VfvzA6GgAAmgUStVaosLxQf3z/j0aHAaC12LhIevV8o6MAAKBZ4WYizcwrVx2jD24ZpowkR1h9WmLkOfcvxb8oEAyEykd1OCpm8QFANQU1rOBb7VLno5s+FgAAmglW1JqZnu1TJUl2a1WOPbxvtiwWS4PGG9h+oG44/IaYxAYA9Rp6i3TQ0VLu4VJ6R6OjAQDAtEy9oub3+3XXXXepe/fuSkpKUs+ePfX3v/9dwWAw1MZisdT430MPPVTruPfcc0+19n379m2KlxQzDwyZqdJNt6jsl6vkdNgaPM6g9oManOQBQNQ6HSn1HUOSBgBAPUy9ovZ///d/evLJJzVr1iz1799fK1eu1Pjx45WRkaEbb7xRkrR9+/awPu+//76uuOIKjR07ts6x+/fvr0WLFoXKdrupp6KazmldFajYZHQYAAAAAOLA1NnJZ599pjPPPFOnnnqqJKlbt2569dVX9cUXVXcNy8nJCevz9ttv66STTlKPHj3qHNtut1fr2xy8vXqbyiv8cnv9RocCAAAAIE5MnagNGTJETz/9tDZs2KA+ffrom2++0SeffKLp06fX2H7Hjh167733NGvWrHrH/vHHH5Wbmyun06nBgwfr/vvvV5cuXWpt7/F45PF4QmWXyyVJ8nq98nq9Ub6ycPv6RzLOtHnrtMPlUfvUhFBdIBCIKgafz9fgvi1FNHO+P7uCskgKKihfK5y3xmrovKNxjJ53a8CvfSdo+3x+BVvJ+2/0vLdWzLsxmHdjMO/GaKr5tgT3v+DLZAKBgO688049+OCDstls8vv9uu+++zR58uQa2z/44IN64IEHlJeXJ6fTWeu477//vkpKSnTwwQdr+/btmjJlirZt26Y1a9YoLS2txj733HOPpkyZUq1+9uzZSk5ObtgLbIC7V9lUVGFRWpuv5Q56FQwk6FDHYRrfJ1B/59/87PtZz5Q8I0k6LvE4/T7p9/EKt8UZ8uP9SvS55LGn67PeNX8OAYTrteM99c97TZL0RfcbtT2TO80CAJqvsrIyXXTRRSoqKlJ6enrcjmPqRG3OnDm67bbb9NBDD6l///5avXq1br75Zk2fPl3jxo2r1r5v374aOXKkZsyYEdVx9u7dq65du2r69Om64ooramxT04pa586dtWvXrka/QV6vVwsXLtTIkSPlcDjqbDv0oaXa4fIorff9kr1IAW+6hiU+pscvGBjx8VbvXK3LF14uSbqk7yW65YhbGhV/cxTNnCN2mHdjGD3v1uWPy/bhvZIk39hZCvY9tcljMILR895aMe/GYN6Nwbwbo7CwUB07dox7ombqUx9vu+023XHHHbrgggskSQMGDNDPP/+s+++/v1qi9vHHH2v9+vV67bXXoj5OZmam+vTpo40bN9baJjExUYmJidXqHQ5HzP5iRDKWRdXv0Gi1WqOKYf8bp0Tbt6WJ5fuHyDHvxjBs3q1Vd6a1221SK3vv+bwbg3k3BvNuDOa9aTXVXJv69vxlZWWyWsNDtNlsCgSqn+b33HPP6cgjj9TAgZGvLO1TUlKiTZs2qWNHbhcNAAAAwHimTtROP/103XfffXrvvfe0ZcsWvfXWW5o+fbrOPvvssHYul0uvv/66rrzyyhrHGT58uJ544olQ+dZbb9XSpUu1ZcsWffbZZzr77LNls9l04YUXxvX1mMHPrp/17c5vjQ4DQKti2jPsAQAwLVOf+jhjxgzddddduu6661RQUKDc3Fxdc801uvvuu8PazZkzR8FgsNZEa9OmTdq1a1eovHXrVl144YUqLCxU+/btNXToUK1YsULt27eP6+sx2ke/fqQbPrzB6DCatzevlMoKpeR20thnjY4GaB4+esDoCAAAaHZMnailpaXp0Ucf1aOPPlpnu6uvvlpXX311rfu3bNkSVp4zZ04MojOPHwuKI2r3+fbPq9X1zOwZ63Bati2fSsV5Ulqu0ZEAzUdmF2nXhsrtrIONjQUAgGbC1IkaInNcr6yI2gWCVdf2je09VkflHKXR3UbHKywAqGTZ7yz79n2MiwMAgGaERM1k3vt2u6YvXK9Sjz9Ud1LfbN1/zgBJUvu0yjtPltqLQvuTE2yKRHC/60T+0OcPOjTr0FiE3Hx8/5a0ZJrkKZFdQY1yu2Xf+Gdp3500J60Lb//RA9KqAx6eXpLfJKECLVJCzc+pBAAA1ZGomcz0heu1aWdpWF1ReUVoe+4NQyVJA37LH4KB6o8MqM3+j8yr6Tb/Ld6SaaHTryySkiSprgfLu12VpznWJDE1xsEBAAAAVUjUTGbfSprVImWnOSVJGUkJ1dp1Semjzbv3qGLnKKlrZGPvv6LWGvM0eUoq/7RYFUztILfbLafTWXvS6kyv+Vq0xFTppL/EL04AAAC0eiRqJpWd5tSKO4fXuv8vg/6li56tfnOQSLXKFbV9UnPku/FbfTBvnsaMGVP7QwtPvKPyPwAAAKCJkag1I1OWT1GRp0gZiRka2f56o8MBAAAAECckas3Isq3LVFBWoOzk7AYlaq3+GrVznpb8HskW+XV9AAAAgBFI1FqR/a9Rs1haYaLW/fiqbW9ddxEBAAAAjEWiZjJnDMpVUZlXGcm1XDfVCGGJWmtcUQMAAACaCRI1k7lzzCERtSsqj35FaP9THwG0Qp5iqSJQf7tYC/ia/pgAADRzJGrNUFGZV9e+8lWjxmiVpz5u/rjqGrWDjjU6GqBJ9c17Q/aHL5OCBiRqAAAgaiRqzVC51x9W3ve8tfq0+lMf/3t15QOs03KlG781OhqgSXXb9aEsRidpaR2MPT4AAM0IiVozd/WwHjrniE4RteXUR6D1suq3JM2RInUf1vQBOJKko69u+uMCANBMkaiZzMkPf6QCl0fZ6Yn6cNKJdbftmx3xNW0HapUragCkjE7SRXOMjgIAANTDanQACFfm8avE41OZx19/4yi1+tvzAwAAAM0EK2rNyJjuY7SzdI/eWrWnQf1b/QOvAQAAgGaCRK0ZmXTUJO0prdCc9xc2qP/+K2rkaQAAAIB5cepjK8WKGgAAAGBeJGqtCKc+AgAAAM0DiVorws1EAAAAgOaBa9SakdPfOl0FZTuV3CNZZT9Nirp/2DVqAAAAAEyLRK0ZKfOVqcxXKovV1uixWuWpj5PWVW17vcbFAQAAANSDRK0ZeHnFz3r245+0u51HiiJHm79lvv65+p8q85ZJkoo8RaF9rTJRA8ygeIf01jXSrg1Ndkh7MCiLv6zJjgcAABqPRM1k7jv7ULm9ATkdVZcPPvD+Dyrx+JTSJqj9F9NSEut++2Z+PVNbXFtq3JfkSIpFuACi9d3r0k9LmvSQYb+WSUht0mMDAICGIVEzmeGHdKhWV+LxSar6smWzWjSgU4auGNq9zrFKvaWSJKvFqqykrMq+FptO73l6qAygiVWUVG0ntZXszrgfMqig3G63nJkdZDnhz3E/HgAAaDwStWbEbrPKL6l9WqLmXj404n4dkjvogz98EL/AmouPHpDcLsmZLh0X/c1YgJg75xmp94i4H8bn9eqDefM0ZswYORyOuB8PAAA0HokaWo9Vs6TiPCktl0QNAAAApkaiZjLfbS1ShT+gBJtVAw7KMDocAAAAAAYgUTOZq15cqXyXWznpTq24c7jR4QAAAAAwgLX+JgAAAACApsSKWjPS3nORbj2lh5y2+N8lDgAAAIBxSNSakRT/YRrd7TijwwAAAAAQZ5z6CAAAAAAmQ6IGAAAAACbDqY8mtmlnif61dFOo7LH+rNUFKXLYHOrfrn+dfX91/aqd5TvjHSKASK14Stq8VNq1wehIAABAM0CiZmL/WLBe76/JD5XznU/qkvf3Kjs5W4vPXVxn3xmrZ4S2rRYWTiVJ3Y6Tygql5HZGR4LWZvu30vw/V6+32po+FgAA0CyQqJlYQbEntO2wWZSUYFOxL7K+u8p3hbbP6HlGrENrnsY+W7Xt9RoXB1qfkh3V67L7S10GN30sAACgWWCppZn4+u5RSkpo2G/fLz/08hhHA6DBhtwo3bpRuvZTycGjNgAAQM1YUTOZRZNOUDAY1Ie/LtK9nzyglF5lkqQz35ketkrW4uz6UZoV4crf1UuktJyq8soXpKUP1t+vXU/psncbFh8QKwmpUmp7o6MAAAAmR6JmMqmJlW/Jc98/qQprvqy/rXkWlLlCbVIcKUaEFl8Bn1ScF2Fbf3i5ojSyvs706OMCAAAADECiZlKvnvqqzn/uPW22zZQsPuVkVJ4ileJI0YRBEwyOLg6sdiktN8K2B5wCmpASWd8UVjEAAADQPJComcjzn25RmTeoNKddVx7fQ4nBg1S66XZJ0sJpY2S1WgyOMI6yekuT1jWs71HjK/8DAAAAWggSNRN5/rOftcPlUU66U1ce38PocAAAAAAYhEQNxvv2dclbJjmSpcPONToaAAAAwHAkaiY16/tZ2uX4QY62QXl3H290OPG18O7Km4Gk5ZKoAQAAACJRM60X176o3Y4CJbRNb/mJGgAAAIAwJGotVF5JhLe6B9B4Py+XNi+tfX/hpqaLBQAAtAgkai3UtpJtRocAtA5FW6V/j5GCAaMjAQAALYjV6AAQmWhvze+wOkLbTrsz1uEA2KdwYxRJmkXqPiyu4QAAgJaBFbVmoG9OWoP79srsFcNIANTp0LHSwItq35/VW2rTteniAQAAzRaJWjNgtzX8Qdf7r6wBiLM23aXeI4yOAgAAtAAkaibSv2O6cjO9apeSoM1GBwMAAADAMCRqJvKvPx4uh6NyBWz46wYHAwAAAMAwJGowXmp2+J8AAABAK0eiZlL92vZTfqFTAV+K0aHE3zV1PH8KAAAAaIVI1ExqxvAZ6v3hPHn9QamT0dEAAAAAaEokaiZyzctfa0955c1Enh33O6PDAQAAAGAQEjUT+X67SztcHuWk84BqAAAAoDUjUTOponJv5WmPDVDmLZM34I1xRHE09yapfI+U1EY6/TGjo0FrU5wv5X3d8P75a2IXCwAAwG9I1EwoqKCO//clSu5arKA/RQreEHFff8Cvse+MjWN0cbDhA6k4T0rLNToStDZF26THB0n+CqMjAQAACEOiZkI+f1B+x6+yOVwKeNPVJz0t4r7bS7dra8nWULlXZq94hAi0DFu/iG2Sln1I7MYCAACtGolaM/C30/s3uO8dx9wRw0iAFqzXSKnLsQ3vn9VH6ntq7OIBAACtGomaySUn2JWR5GhQ3993+73SE9JjHBHQQvU4URoywegoAAAAJElWowMAAAAAAIQjUQMAAAAAkyFRAwAAAACT4Ro1E7l8SFeVeYMq8fg0J9/oaAAAAAAYhUTNRC4/rpscDofWbCvSnPeNjgYAAACAUUjUYLwBY6XyvVJSptGRAAAAAKZAomZSFbuPl8Xq1qGdOxodSvyNmmp0BAAAAICpkKiZSInHJ7tfKvX45N19vCSpV6+uBkcFNCMBv1SyI/L2ZbvjFwsAAEAjkKiZyCmPf6odLo8sjRhjR1kUX1KBlqRst/SvE6SiX4yOBAAAoNG4Pb8JBffbzslwRtX3h90/hLYL3YUxighoBjZ92LgkLb0VnGYMAACaDVbUzMrqkRTU2Ue0i66bpSr3HtppaIyDipMZR0nF+VJajnTDSqOjQXMV8Fdtdxggte0eed+cAVLf02IfEwAAQAORqJlUSo+HZXW4dMkH/9Ticxc3aIyspKwYRxUnFaVSRbFUkWZ0JGgpjhwnHX2V0VEAAAA0GImaSXxdaFFh8Esl91goi9Uji73Y6JDq9/1b0pJpkqek5v0XzpZyD68qr58vvXtL9XYlPN0bAAAA2B+Jmkm8/6tVCR0Xypa4M6w+xZFiUEQRWDJN2rWh9v1+b3jZVy4V59XePjE1NnEBAAAAzRyJmkm4/ZLF6pEkBYMWBX1pSktI1YRBEwyOrA77VtIsVik1p/p+myO8bE+S0nJrHisxVTrpL7GNDwAAAGimSNRMKOhLU+nGOzX68E4a1W2Q0eHULzVHmrSu/nYHn1L5HwAAAIA6cXt+AAAAADAZVtRM4qqD/fqPNUF7KoyOJAoTvpCCQcnSmEd0AwAAADgQiZpJdE6VZhz7qPJc5br+lW+MDicyidxOHwAAAIgHEjUT6de2n9JtFQq4C40OBQAAAICBTJ2o+f1+3XPPPXr55ZeVn5+v3NxcXXbZZfrrX/8qy2+n21122WWaNWtWWL/Ro0dr/vz5dY49c+ZMPfTQQ8rPz9fAgQM1Y8YMHX300XF7LZHaVeKJuG0gGNBfPvmLPsv7LFTn9rnjERbQdMp2S29eIeV/F10/L599AADQcpg6Ufu///s/Pfnkk5o1a5b69++vlStXavz48crIyNCNN94YanfKKafohRdeCJUTExPrHPe1117TxIkT9dRTT+mYY47Ro48+qtGjR2v9+vXKzs6O2+upy5o9FlnW5GvxD7tCdS63r84+3+78Vu/+9G6t++P+DLbPnpA8xZWnQA4x8WME0Lysmytt+rBxY3BaLgAAaOZMnah99tlnOvPMM3XqqadKkrp166ZXX31VX3zxRVi7xMRE5eTU8ByvWkyfPl1XXXWVxo8fL0l66qmn9N577+n555/XHXfcEbsXEIX//GTV81tfU1JCQLZUq/wlh+iobm3q7FPuKw9tpznSlJ6YHiof1v4wDe00NG7xSpKWz6x8gHVaLokaYqeitGo7OUtKiPIXDh0Pk/qeGtuYAAAAmpipE7UhQ4bo6aef1oYNG9SnTx998803+uSTTzR9+vSwdh999JGys7PVpk0bnXzyyZo6daratWtX45gVFRVatWqVJk+eHKqzWq0aMWKEli9fXmssHo9HHk/VaYkul0uS5PV65fV6G/MyQ/2dOW/J4nDJ6U1X6cZD1K2ts86x/X5/aPv8PufruoHXhTcISN5A42Kri11BWSQFFZSvkXPQ1PbNa2PfO0Qnknm3Bvyy/bbtGzVNwf7nNPRgDevXAvF5Nwbzbgzm3RjMuzGYd2M01XybOlG744475HK51LdvX9lsNvn9ft133326+OKLQ21OOeUUnXPOOerevbs2bdqkO++8U7///e+1fPly2Wy2amPu2rVLfr9fHTp0CKvv0KGDfvjhh1pjuf/++zVlypRq9R988IGSk5Mb8Sr3qR7rqpWr5PkpWGuPjd6NVdsbN2retnkxiCNyo9xuJUlyu936YF7THjtWFi5caHQIrVJd896jYK0G/La9evVqbfvZ2TRBtQJ83o3BvBuDeTcG824M5r1plZWVNclxTJ2o/ec//9Err7yi2bNnq3///lq9erVuvvlm5ebmaty4cZKkCy64INR+wIABOuyww9SzZ0999NFHGj58eMximTx5siZOnBgqu1wude7cWaNGjVJ6enodPevn9Xp196rq1+QcedSRGt639mvmPs//XP/+8N+SpF69emnMwDGNiiNa9o1/lryS0+nUmDFNe+zG8nq9WrhwoUaOHCmHw2F0OK1GJPNu/eIXaVvl9qBBgzSwf/P6bJkRn3djMO/GYN6Nwbwbg3k3RmFh09yh3dSJ2m233aY77rgjlIwNGDBAP//8s+6///5QonagHj16KCsrSxs3bqwxUcvKypLNZtOOHTvC6nfs2FHndW6JiYk13qTE4XDE7S+G3Wavc+z9VwytNqsBf0Etv/3f0mz/cYjn+4fa1Tnv1qrPtd1mk3h/YobPuzGYd2Mw78Zg3o3BvDetpppra5McpYHKyspktYaHaLPZFAgEau2zdetWFRYWqmPHjjXuT0hI0JFHHqnFixeH6gKBgBYvXqzBgwfHJnAAAAAAaARTJ2qnn3667rvvPr333nvasmWL3nrrLU2fPl1nn322JKmkpES33XabVqxYoS1btmjx4sU688wz1atXL40ePTo0zvDhw/XEE0+EyhMnTtQzzzyjWbNmad26dbr22mtVWloaugskAAAAABjJ1Kc+zpgxQ3fddZeuu+46FRQUKDc3V9dcc43uvvtuSZWra99++61mzZqlvXv3Kjc3V6NGjdLf//73sNMUN23apF27qp5Pdv7552vnzp26++67lZ+fr0GDBmn+/PnVbjACAAAAAEYwdaKWlpamRx99VI8++miN+5OSkrRgwYJ6x9myZUu1ugkTJmjCBJ79BQAAAMB8TJ2otSaJVslvsRgdRnQ6DpQyOlU+lBgAAABAzJComcRfDvfr2UAb/VzkUTBQ/e6SNVmeV/sDupvERXOMPT6Ms/lj6Yt/Sd7yqLrZAkEdu3OnbK/Okqy1/GJi7y8xCBAAAKB5I1EzkZdH/UcD/171PDW7re4Vthe+f6GqrZW3Ek1o7o3S7p+i7maV1EGSiiPsYONWwwAAoHUy9V0fW5sSjz+sfGyPdnW2t1qq3r7RXUfX0RKIsZKd8T9G+75Sj5PifxwAAAATYhnGRILBYGh7dP8OcjpsdbSuckjbQ9Qjs0e8wgJq1663dOWiiJt7fT598MEHGjVqlBz2ev75cWZIze26TQAAgBghUTOJt7dYtbBkQ6hsUeRfUG2WyBK6mJt9gVS2q/JmIlyv1jpZbVJSZuTtvV757CmVSZiD0xoBAABqQ6JmEqsKLXL7n1dixzLJnyzpcqNDqt/2b6TiPCkt1+hIAAAAgBaFRM1E7OmrZXW4FPCmGx0KAAAAAANxMxGT4tIcAAAAoPUiUQMAAAAAkyFRMylW1AAAAIDWi0QNAAAAAEyGRM2kork9PwAAAICWhbs+NlPbS7YrEAwYHQbMbvu30rq5UtAf23F97tiOBwAAgDAkas3Unz/+s9EhwOy85dKs0yX3XqMjAQAAQJRI1Eyif2ZQP9ht8u6rqOfMxy1FW0LbQw8aGq+w6jb4eslTLCWmGXN81K10V/yTtF4j4js+AABAK0WiZhLn9wzo47Rhevf7nxT0J0nJkfe9buB18QusLkMmGHNcRK/rcdIJMV6FdWZIHQfGdkwAAABIIlEzlQkDbtcbH3wsSbJkR9anc1pnWbiXP+qT0l7qcYLRUQAAACBCJGom8P6afD3xvVVPD46g8fdvSUumSSnlktUi7f1FevgQacBYadTU8LYzjpIqSusf87RHpINPqSrnfS29elFkwU/4glMfAQAAgBgjUTOBRxdvUqHbovyiqjvp1bpKtmSatGuDlNxJkk0K+KTi7VL53upti/OliuL6A/CVh5f9Xqk4L7Lgg8HI2gEA8P/t3XlYVNX/B/D3MCzDjqhsKoKySCYKigquJQqhhAthxS8h11IiM0utr4gLoiZkapqlQYvlUmqWS7mAqZkrLoUiIogWSG4gsg0z9/cHcXNkX2fQ9+t55mnuveee+7mH68x8OueeS0REtcZETQM8KCmF3GY1XjucDwM7IxRkvFF14eJ81WUtbcDYBtA3q1jW2AooqUVvl7a+6rJUp6zO2uCwSyIiIiKiRsdETUNItO9DKc2DRLush6rG9Efy77PKzWyB8bsrL/PGqfoFY+MGvH2xfvsSEREREVGDaak7ACIiIiIiIlLFRI2IiIiIiEjDcOijhqry1i+nYUDhXaDoD0CQV1GIiIiIiIhaMiZqLUzusAU4lX0KJUffB+RM1J54SgWQcQQouldx24NbzR4OERERETUOJmoaqrIOtRJFCQJ2BOB20e1mj4c01J5ZwMnP1B0FERERETUy3qPWgmTmZVZI0pxaOakpGtIImcdqV87y6aaNg4iIiIgaFXvUNFSVD7z+19Otn8YYpzEY2nFoM0VEGk0iBbwjK99mYgO4+DdrOERERETUMEzUNMC7w5yw5A+gqA77ON1MReCIwCaLiVoYqQ7QL1zdURARERFRI2GipgGe726NP9N90MbeHrG/ZNZup9LCpg2KiIiIiIjUhveoaYjuut0xtL0/SvN6AKh8MhEiIiIiInoyMFHTIIKg7giIiIiIiEgTcOijBrj6zwNkFQBGdwv+W8kuNSIiIiKiJxYTNQ0wLv4UcoruotW1A5DoKiCUtFV3SEREREREpEZM1DSEge1nkOvkwUBuggdX3oOEXWpERERERE8s3qNGRERERESkYdijpqFqeN41PYnuZwOljzxtr7RYPbEQERERUZNiotaC3Mi/oe4QSF12zQROfqbuKIiIiIiomXDoo4a6mVdUYV1Gbob4/o5ll2aMhtTu7DfVbzdp1zxxEBEREVGzYI+ahvLs3LrCOqmWVHzfv0tQc4ZD6iYoyv6rZwo4DlXdpiMDeo5v/piIiIiIqMkwUdNQrQx0q91uqmfaTJGQRjGzBQI3qDsKIiIiImpiHPpIRERERESkYdij1lLdz1J3BERERESNTqFQQC6XqzuMFkEul0NbWxtFRUVQKBTqDuexoaOjA6lUWnPBJsZETQNse60vAn8E8uuy06EPANdXmyokIiIiomYlCAKys7Nx7949dYfSYgiCACsrK1y/fh0SPtupUZmZmcHKykqt7cpETQNYGOthmsnryG/TBUt/TlV3OERERETNrjxJs7CwgIGBAROPWlAqlcjPz4eRkRG0tHhHU2MQBAEFBQXIyckBAFhbW6stFiZqGsJYyxhaOm0glN5UdyhEREREzUqhUIhJWuvWFWe+psoplUqUlJRAJpMxUWtE+vr6AICcnBxYWFiobRgk/6JEREREpFbl96QZGBioORKiMuXXojrvl2SPmgbYdPIGTv8tAQrvqDsUIiIiIrXhcEfSFJpwLTJR0wCrE9NwR+sUZIW/Q8dMG/J7fdQdEhERERERqRETNQ2h2+YAoJMHXblJpYmaUlBi2cllaoiMGux0PJC4BJAX1L+O0qJGC4eIiIg0m52dHaZPn47p06erO5QGk0gk2L59O0aOHImMjAzY29sjKSkJPXr0UHdoGo/3qGkoY5lqDn3+n/Mqy0ZCc0ZDDZK4pOy5d0W59X+Vk5mo7zyIiIhIhUQiqfYVGRlZr3pPnjyJyZMnNyi2wYMHq8RiaWmJF154AdeuXWtQvQ3RoUMHZGVl4emnn1ZbDC0Je9Q0lLeLpcpykUK1R6WvnJlai1Hek6alA7Syq389+mbA4NmNERERERE1gqysLPH95s2bERERgZSUFHGdkZGR+F4QBCgUCmhr1/zzu23bto0S36RJk7BgwQIIgoBr165h+vTp+L//+z8cPny4UeqvK6lUCisrK7UcuyVij5oG6tbOFDKdqqcBnXQvlxl2S9TKDnjjVP1fE/cD9gPVfRZERET0LysrK/FlamoKiUQiLl+6dAnGxsbYs2cPevbsCT09PRw5cgRpaWkICAiApaUljIyM4OHhgf3796vUa2dnhxUrVojLEokE69evx6hRo2BgYABHR0fs3LmzxvgMDAxgZWUFa2tr9O3bF2FhYThz5oy4XaFQYMKECbC3t4e+vj6cnZ3x0UcfqdSRmJiI3r17w9DQEGZmZujXr59Kr9wPP/wAd3d3yGQydOrUCfPnz0dpaWml8WRkZEAikeDs2bNi3RKJBAcOHECvXr1gYGAALy8vlWS3rsd4nDBRa4l6TwEmJ6g7CiIiIiKqwezZs7FkyRJcvHgRrq6uyM/Ph5+fHw4cOICkpCT4+vrC398fmZmZ1dYzf/58BAUF4fz58/Dz80NwcDDu3Kn9jOF37tzBli1b0KfPf3MhKJVKtG/fHlu3bkVycjIiIiLw3nvvYcuWLQCA0tJSjBw5EoMGDcL58+dx7NgxTJ48WZwR8fDhwxg3bhzefPNNJCcnY926dYiPj0dUVFSd2uj9999HTEwMTp06BW1tbYwfP17c1ljHaInYMdMS/Lkd+HUhUP5oET1jwJjdxkRERPR48191BP/cL27WY7Y11sOPb/RvtPoWLFiAoUOHisvm5ubo3r27uLxw4UJs374dO3fuRFhYWJX1hIaG4qWXXgIALF68GCtXrsSJEyfg5eVV5T5r1qzB+vXrIQgCCgoK4OTkhJ9//lncrqOjg/nz54vL9vb2OHbsGLZs2YKgoCDk5eUhNzcXI0aMQOfOnQEALi4uYvn58+dj9uzZCAkJAQB06tQJCxcuxLvvvot58+bVtokQFRWFQYMGAShLbIcPH46ioiLIZLJGO0ZLxEStJUhYDOTfAAwsay5LRERE9Jj4534xsvNa9szHvXr1UlnOz89HZGQkdu3ahaysLJSWlqKwsLDGHjVXV1fxvaGhIUxMTJCTk1PtPsHBwXj//fcBADdv3sTixYsxbNgwnD59GsbGxgCAjz/+GJ9//jkyMzNRWFiIkpIScUZGc3NzhIaGwsfHB0OHDoW3tzeCgoJgbW0NADh37hyOHj2q0rulUChQVFSEgoKCWj/A/OFzK687JycHtra2jXaMloiJWktQnK/uCIiIiIiaXVtjvRZ/TENDQ5XlmTNnYt++fVi+fDkcHBygr6+PwMBAlJSUVFuPjo6OyrJEIoFSqax2H1NTUzg4OAAAHBwcsGHDBlhbW2Pz5s2YOHEiNm3ahJkzZyImJgaenp4wNjbGBx98gOPHj4t1xMXFITw8HHv37sXmzZvxv//9D/v27UPfvn2Rn5+P+fPnY/To0RWOLZPJqo2tqnMrH1ZZfm6NdYyWiImaBrBvbYBkCcB5HImIiIj+05hDEDXF0aNHERoailGjRgEoS0QyMjKa5dhSadlkdYWFhWIsXl5emDp1qlgmLS2twn5ubm5wc3PDnDlz4OnpiW+++QZ9+/aFu7s7UlJSxGSwKTTHMTQVEzUN8NV4D4zZ0hppD2RQlhrVvAMRERERtUiOjo7Ytm0b/P39IZFIMHfu3Bp7xuqroKAA2dnZAMqGPi5cuBAymQzDhg0TY/nyyy/x888/w97eHl999RVOnjwJe3t7AEB6ejo+/fRTPP/887CxsUFKSgpSU1Mxbtw4AEBERARGjBgBW1tbBAYGQktLC+fOncMff/yBRYsWNco5NMcxNBVnfdQQE4wmoDjjbRRmNuzhhkRERESkuWJjY9GqVSt4eXnB398fPj4+cHd3b5JjffbZZ7C2toa1tTWeeeYZ3Lp1C7t374azszMAYMqUKRg9ejTGjh2LPn364Pbt2yq9awYGBrh06RLGjBkDJycnTJ48GdOmTcOUKVMAAD4+Pvjpp5/wyy+/wMPDA3379sWHH36Ijh07Nto5NMcxNBV71IiIiIiIGig0NBShoaHi8uDBgyEIFW9ssbOzw8GDB1XWTZs2TWX50aGQldVz7949KJVK5OXlVRpPYmJijTHr6ekhLi4OcXFxKuujo6MBAJaWlti+fXu1dfj4+MDHx6fK7Q/Hbmdnp7JcWRv16NGjwrqajvG4YqKmIQQBKFVW/EeoFJT4xEALCdJWaoiKVKQlAMc/AeQFdduPk8EQERERUR0xUdMAM7aex7mr/41CLZIrxPdnbp7BWgMtALriOh2p6qw/1Ex+mg7czaj//lLdmssQEREREYGJmkY4kXEXuSZboN/qAQSFIaTKSeK2O0WqT5y3MbSBj92T1/WrER7cqv++2vpA70k1lyMiIiIiAhM1jSE1uAotnTwo5SYY6diu0jLhghkmjNkDLQnngFGrNs7A5MS67aOlDWizR42IiIiIaoeJmgaSVLFep9cEJmmaQKIF6BqoOwoiIiIieozxV78GklSVqRERERER0ROBiZoGklTZp0ZERERERE8CJmpEREREREQahomaBqpy6OOFrc0aBxERERERqQcTtZbkbrq6IyAiIiIiUpGYmAiJRIJ79+4BAOLj42FmZqbWmB4HTNSIiIiIiOpBIpFU+4qMjGxQ3Tt27KixXKtWrSCVSiGRSKCtrQ1bW1vMmDEDxcXF9T52Q40dOxaXL19W2/EfF5yeXwOM7dkeX/4FKP5dlnDaRyIiIiKNl5WVJb7fvHkzIiIikJKSIq4zMjJqljg2bNgAPz8/yOVynDt3Dq+++ioMDQ2xcOHCZjn+o/T19aGvr6+WYz9O2KOmAd54tjMc0Qslt/tDfq83JABOZZ9C7KlY/Jj2o7rDe3Io5MCZr4Bf/lf5q7RI3RESERGRBrGyshJfpqamkEgkKus2bdoEFxcXyGQydOnSBWvWrBH3LSkpQVhYGKytrSGTydCxY0dER0cDAOzs7AAAo0aNgkQiEZerYmZmBisrK3To0AEjRoxAQEAAzpw5I25PS0tDQEAALC0tYWRkBA8PD+zfv1+ljjVr1sDR0REymQyWlpYIDAwUtymVSkRHR8Pe3h76+vro3r07vvvuuyrjeXToY2RkJHr06IGvvvoKdnZ2MDU1xYsvvoj79+/X+xhPAvaoaQgXYQhO5kgBAEXKPEzeNxlypVylDPvZmtgf24CdYTWXY48nERER1WDjxo2IiIjA6tWr4ebmhqSkJEyaNAmGhoYICQnBypUrsXPnTmzZsgW2tra4fv06rl+/DgA4efIkLCwsEBcXB19fX0il0lof9/Llyzh48CBCQ0PFdfn5+fDz80NUVBT09PTw5Zdfwt/fHykpKbC1tcWpU6cQHh6Or776Cl5eXrhz5w4OHz4s7h8dHY2vv/4an3zyCRwdHfHrr7/i//7v/9C2bVsMGjSoVnGlpaVhx44d+Omnn3D37l0EBQVhyZIliIqKarRjPG6YqGkIQfjvfZ78nwpJmo4goG+JAGpCd9JqV87Jp2njICIiItH6w1ex/nDNE6o93c4E60M8VNZN/OIk/vgrr8Z9Jw6wx8QBneodY2XmzZuHmJgYjB49GgBgb2+P5ORkrFu3DiEhIcjMzISjoyP69+8PiUSCjh07ivu2bdsWwH89ZTUJDg6GVCpFaWkpiouLMWLECMyZM0fc3r17d3Tv3l1cXrhwIbZv346dO3ciLCwMmZmZMDQ0xIgRI2BsbIyOHTvCzc0NAFBcXIzFixdj//798PT0BAB06tQJR44cwbp162qdRCmVSsTHx8PY2BgA8Morr+DAgQOIiopqtGM8bpioaaCH+2ucWjnh/fRk2OVmw9yw5n+o1EiGRQHtelZcLzMFLJ9q/niIiIieUPeLSpGdV/PtB9Zmsgrrbj8oqdW+94tK6xVbVR48eIC0tDRMmDABkyZNEteXlpbC1NQUABAaGoqhQ4fC2dkZvr6+GDFiBIYNG1av48XExGDYsGFQKBS4cuUKZsyYgVdeeQWbNm0CUNajFhkZiV27diErKwulpaUoLCxEZmYmAGDo0KHo2LEjOnXqBF9fX/j6+mLUqFEwMDDAlStXUFBQgKFDh6ocs6SkREzmasPOzk5M0gDA2toaOTk5ANBox3jcMFHTAP0/OISbef91aT88ss7Nwg3uqcmAUqmGyJ5gFi5AR091R0FERPTEM5Zpw8qkYhL2qNaGupWuq82+xrLG/Umcn58PAPjss8/Qp08flW3lwxjd3d2Rnp6OPXv2YP/+/QgKCoK3t3e97suysrKCg4MDAMDZ2Rn379/HSy+9hEWLFsHBwQEzZ87Evn37sHz5cjg4OEBfXx+BgYEoKSkBABgbG+PMmTNITEzEL7/8goiICERGRuLkyZPiuezatQvt2rVTOa6enl6tY9TR0VFZlkgkUP77+7axjvG4YaKmIQwdFkNLJw9KuQmA+eoOh4iIiEgjTBzQqd7DEh8dCtlcLC0tYWNjg6tXryI4OLjKciYmJhg7dizGjh2LwMBA+Pr64s6dOzA3N4eOjg4UCkWV+1anPBksLCwEABw9ehShoaEYNWoUgLLEKCMjQ2UfbW1teHt7w9vbG/PmzYOZmRkOHjyIoUOHQk9PD5mZmU02BPGpp55q8mO0REzUNFCFuSp6hgBFeYDMRC3xEBEREVHdzJ8/H+Hh4TA1NYWvry+Ki4tx6tQp3L17FzNmzEBsbCysra3h5uYGLS0tbN26FVZWVuJsiXZ2djhw4AD69esHPT09tGrVqspj3bt3D9nZ2VAqlUhNTcWCBQvg5OQEFxcXAICjoyO2bdsGf39/SCQSzJ07V+zNAoCffvoJV69excCBA9GqVSvs3r0bSqUSzs7OMDY2xsyZM/HWW29BqVSif//+yM3NxdGjR2FiYoKQkJAGt1VzHKMlYqLWEgyere4IiIiIiKgOJk6cCAMDA3zwwQd45513YGhoiG7dumH69OkAypKTZcuWITU1FVKpFB4eHti9eze0tMqenhUTE4MZM2bgs88+Q7t27Sr0gD1swoQJACA+HmDgwIFYvHgxtLXLfurHxsZi/Pjx8PLyQps2bTBr1izk5f03yYqZmRm2bduGyMhIFBUVwdHREd9++y26du0KoGzykbZt2yI6OhpXr16FmZkZ3N3d8d577zVaezXHMVoaiSAInEqwHvLy8mBqaorc3FyYmDSsp6vP4v3It5gnDn0MdViAL69NBwCMdR6L//X9XyNETA+Ty+XYvXs3/Pz8/hsznbAYOLS07P3/bQMchqgvwMdUpe1OTY7trh5sd/Vgu6tHQ9u9qKgI6enpsLe3h0xW8z1lVEapVCIvLw8mJiZigkeNo7pr8vbt22jTpk2j5AHV0ei/qEKhwNy5c8UH33Xu3BkLFy5EeW4pl8sxa9YsdOvWDYaGhrCxscG4cePw999/V1tvZGQkJBKJyqtLly7NcUpEREREREQ10uihj0uXLsXatWvxxRdfoGvXrjh16hReffVVmJqaIjw8HAUFBThz5gzmzp2L7t274+7du3jzzTfx/PPP49SpU9XW3bVrV5Unspd3DWsCPk6ZiIiIiOjJpjnZSSV+++03BAQEYPjw4QDKbqr89ttvceLECQCAqakp9u3bp7LP6tWr0bt3b2RmZsLW1rbKurW1tWv1AEF1qDCZSIwLcP9vwNgGePuiWmIiIiIiIqLmo9GJmpeXFz799FNcvnwZTk5OOHfuHI4cOYLY2Ngq98nNzYVEIhFnzKlKamoqbGxsIJPJ4Onpiejo6GoTu+LiYhQXF4vL5TdgyuVyyOXyup3Yox65S1Cp+G8WHqVSCQECJAAECCht6LGeVEW5kKQnAsqyB1oqSxVod+cClOfyUapdNoWtVvYf4ljgUoUCAtu60ZX/W2nwvxmqE7a7erDd1YPtrh4NbXe5XA5BEKBUKlVmI6Tqld8OVN521HiUSiUEQYBcLhcfd1CuuT5fNHoyEaVSiffeew/Lli2DVCqFQqFAVFQU5syZU2n5oqIi9OvXD126dMHGjRurrHfPnj3Iz8+Hs7MzsrKyMH/+fPz111/4448/VJ6Y/rDIyEjMn1/x+WbffPMNDAwM6neC/4o4LUWpbbQ4mYiLxBMp2j8DAPro9sGqq/uhL7+LQp1W+OXpjxp0rCeSoMSQi7NgVHyz1rv81vkd/GPSrQmDIiIionLlI506dOgAXd2KD64mam4lJSW4fv06srOzUVpaqrKtoKAAL7/8cpNPJqLRPWpbtmzBxo0b8c0336Br1644e/Yspk+fDhsbmwrPU5DL5QgKCoIgCFi7dm219T733HPie1dXV/Tp0wcdO3bEli1bxOlNHzVnzhzMmDFDXM7Ly0OHDh0wbNiwBv+BTB1zMOM4UJ6bt7YwA+6UvbdsbwnZ3zJADshkMvj5+TXoWE+kB7egc7b2SZogkcJj+DjA2LoJg3oyyeVy7Nu3D0OHDuVsbM2I7a4ebHf1YLurR0PbvaioCNevX4eRkRFnfawDQRBw//59GBsbQ1Lh3hlqiKKiIujr62PgwIGVzvrYHDQ6UXvnnXcwe/ZsvPjiiwCAbt264dq1a4iOjlZJ1MqTtGvXruHgwYN1TpzMzMzg5OSEK1euVFlGT08Penp6Fdbr6Og0+Iugn6MFeh59AQezBUCQQss6X9zma+8LyYltAAAJJPzSqY+H26ytC9AzFAqlAsl/JuOprk9BqqXanS2xHwAd86qHwVLDNca/G6o7trt6sN3Vg+2uHvVtd4VCAYlEAi0tLU4zXwflwx3L244aj5aWFiQSSaXXdHN9tmh0olZQUFDhopNKpSpjcMuTtNTUVCQkJKB169Z1Pk5+fj7S0tLwyiuvNDjm+motdILiQXnCcE5cL5VIK9+B6qeVHdD3NSjlclz9Zze6ePhByi9yIiIiItIwGp16+/v7IyoqCrt27UJGRga2b9+O2NhYjBo1CkBZkhYYGIhTp05h48aNUCgUyM7ORnZ2NkpKSsR6hgwZgtWrV4vLM2fOxKFDh5CRkYHffvsNo0aNglQqxUsvvdTs51ju4RsFVTquv58I5Gc3czRERERERKROGp2orVq1CoGBgZg6dSpcXFwwc+ZMTJkyBQsXLgQA/PXXX9i5cydu3LiBHj16wNraWnz99ttvYj1paWm4deuWuHzjxg289NJLcHZ2RlBQEFq3bo3ff/8dbdu2bfZzBICvzh5ESkkqpAZp/655KFUrvA0I//Yg6hk1e2xERERE1Lzs7OywYsUKdYdRQXx8fI0zqz8qNDQUI0eObJJ4KqOpbVcfGj300djYGCtWrKiyse3s7FCbSSszMjJUljdt2tQI0TWeFRcWQjDOhYnMAN2uBsCw8O//Nuq3BrSFsiTtmffVFyQRERERqahpAo958+YhMjKyzvWePHkShoaG9YwKmD17Nnbs2IFLly6J6y5dugQXFxeEhIQgPj5eXB8fH48pU6bg3r170NfXr7besWPHNsnEdnZ2dpg+fTqmT5/e6HW3ZBqdqD1pzCT5+FJ3KVZk2wDG//5pxqwH2nmpNzAiIiIiqiArK0t8v3nzZkRERCAlJUVcZ2T032goQRCgUCigrV3zz++GjvJ65plnsHTpUmRnZ8PKygoAkJCQgA4dOiAxMVGlbEJCAvr27VtjkgYA+vr6tSpHjUOjhz4SEREREWkqKysr8WVqagqJRCIuX7p0CcbGxtizZw969uwJPT09HDlyBGlpaQgICIClpSWMjIzg4eGB/fv3q9T76PA9iUSC9evXY9SoUTAwMICjoyN27txZZVz9+/eHjo6OSlKWmJiIadOm4c6dOyqjzRITE/HMM88AAIqLizFz5ky0a9cOhoaG6NOnj0odlQ19XLRoESwsLGBsbIyJEydi9uzZ6NGjR4WYli9fDmtra7Ru3RrTpk0THxo9ePBgXLt2DW+99RYkEolKL+WRI0cwYMAA6Ovro0OHDggPD8eDBw/E7Tk5OfD394e+vj7s7e2rfY5yS8REjYiIiIioicyePRtLlizBxYsX4erqivz8fPj5+eHAgQNISkqCr68v/P39kZmZWW098+fPR1BQEM6fPw8/Pz8EBwfjzp07lZY1NDSEh4cHEhISxHWJiYkYMmQI+vXrJ66/evUqMjMzxUQtLCwMx44dw6ZNm3D+/Hm88MIL8PX1RWpqaqXH2bhxI6KiorB06VKcPn0atra2lT7POCEhAWlpaUhISMAXX3yB+Ph4cfjltm3b0L59eyxYsABZWVliL2VaWhp8fX0xZswYnD9/Hps3b8aRI0cQFhYm1hsaGorr168jISEB3333HdasWYOcnJxq27El4dBHIiIiItJM6wYB+c38w9vIAphyqNGqW7BgAYYOHSoum5ubo3v37uLywoULsX37duzcuVMlCXlUaGioOEP54sWLsXLlSpw4cQJeXpXfIvPMM89g69atAIDk5GQUFRXBzc0NAwcORGJiIl599VUkJiZCJpOhb9++yMzMRFxcHDIzM2FjYwOgbKb0vXv3Ii4uDosXL65wjFWrVmHChAl49dVXAQARERH45ZdfkJ+fr1KuVatWWL16NaRSKbp06YLhw4fjwIEDmDRpEszNzSGVSmFsbCwO0wSA6OhoBAcHi/etOTo6YuXKlRg0aBDWrl2LzMxM7NmzBydOnICHhwcAYMOGDXBxcamyDVsaJmoaqObpUagCRSlw52rl2wrvNm8sRERE1Djyc4D7f9dcToP16tVLZTk/Px+RkZHYtWsXsrKyUFpaisLCwhp71FxdXcX3hoaGMDExqbb3aPDgwYiKikJWVhYSExPRv39/SKVSDBo0CJ988gmAsl42Ly8v6Onp4cKFC1AoFHByclKpp7i4uMrnFKekpGDq1Kkq63r37o2DBw+qrOvatSuk0v+eDWxtbY0LFy5Ue77nzp3D+fPnVYYzCoIApVKJ9PR0XL58Gdra2ujZs6e4vUuXLnWelVKTMVHTQJ8b889SJyUPgDV9gXvVf8ARERFRC2Nk0eKP+ejsjTNnzsS+ffuwfPlyODg4QF9fH4GBgSrPAK6Mjo6OyrJEIoFSqayyfL9+/aCrq4uEhAQkJCRg0KBBAAAPDw/cunULV69eRWJiIqZMmQKgLIGUSqU4ffq0SlIFqE6KUh91jb08nilTpiA8PLzCNltbW1y+fLlBMbUEzAg0TP4j07xaGVlVUZJE14/XPkkz69C0sRAREVHjacQhiJri6NGjCA0NxahRowCUJSSPPkqqMejr64uTgRw6dAjvvPMOgLKkqW/fvtiwYQOuX78u3p/m5uYGhUKBnJwcDBgwoFbHcHZ2xsmTJzFu3Dhx3cmTJ+scq66uLhQKhco6d3d3JCcnw8HBodJ9unTpgtLSUpw+fVoc+piSkoJ79+7V+fiaiomahlE+8jiOTqad1BNISyI89H9kLLsBVt0qL2dsCfSdWvk2IiIiombg6OiIbdu2wd/fHxKJBHPnzq2xd6m+nnnmGXz44YcAyhKfcoMGDcLy5cvFSUcAwMnJCcHBwRg3bhxiYmLg5uaGf/75BwcOHICrqyuGDx9eof433ngDkyZNQq9eveDl5YXNmzfj/Pnz6NSpbr9f7ezs8Ouvv+LFF1+Enp4e2rRpg1mzZqFv374ICwvDxIkTYWhoiOTkZOzbtw+rV6+Gs7MzfH19MWXKFKxduxba2tqYPn36Y/X4AM76qMH6teun7hBani7DgVFrK395R6pnCAURERHRv2JjY9GqVSt4eXnB398fPj4+KklUY3rmmWdw//599OvXT+X5bYMGDcL9+/fFafzLxcXFYdy4cXj77bfh7OyMkSNH4uTJk7C1ta20/uDgYMyZMwczZ86Eu7s70tPTERoaCplMVqc4FyxYgIyMDHTu3Fl8hpyrqysOHTqEy5cvY8CAAXBzc0NERIQ40Ul5vDY2Nhg0aBBGjx6NyZMnw8Li8fmtJxEEgXNX1ENeXh5MTU2Rm5sLExOTBtUll8vxfMxefF4YDkPpXfTrWDY8r1+7fvjE+5PGCPfxdmU/8PWYsveDZgPPzKlxF7lcjt27d8PPz6/CuGlqOmx39WC7qwfbXT3Y7urR0HYvKipCeno67O3t6/wj/0mmVCqRl5cHExMTaGlpRv/L0KFDYWVlha+++krdoTRIddfk7du30aZNm0bJA6rDoY8aQhAAz+LVgFYhjDFf3eEQEREREVWroKAAn3zyCXx8fCCVSvHtt99i//792Ldvn7pDeywwUSMiIiIiojqTSCTYvXs3oqKiUFRUBGdnZ3z//ffw9vZWd2iPBSZqRERERERUZ/r6+ti/f7+6w3hsMVHTAON3LsHfBn9BV0cfJXc4gQgRERER0ZOOiZoGOJf7MwSzXLSS62Bc3g1w+hAiIiIioiebZkwPQwAAA0kxXtHmzZdERERERE86JmpEREREREQahkMfNYwAibpDqKjgDvDti0DWeXVHUjlBoe4IiIiIiIgaFRM1DXPloYdE3iq4pcZIHnLpJ+D6cXVHUTv6ZuqOgIiIiIiowZioaRjlQx1qbQzaqC+Qh8mL/ntv0g6QmaktlGq1dQa6Bak7CiIiIqIWLTQ0FPfu3cOOHTtqvY+dnR2mT5+O6dOnN1lc5TIyMmBvb4+kpCT06NGjyY+nLkzUNJhzK2d1h1CRdyTgymSIiIiISCKp/paVefPmITIyst51b9++HSNHjqyyjJeXF1xcXLBhwwZx3SeffILXX38dcXFxCA0NFdeHhoYiLS0Nhw8frvHYH330EQRBqFfcVXlSkqvGxMlEiIiIiIjqISsrS3ytWLECJiYmKutmzpzZpMcfPHgwjh49qrIuISEBHTp0QGJiosr6xMREPPvss7Wq19TUFGZmZo0UJdUXEzUiIiIionqwsrISX6amppBIJCrrNm3aBBcXF8hkMnTp0gVr1qwR9y0pKUFYWBisra0hk8nQsWNHREdHAygbRggAo0aNgkQiEZcfNXjwYKSmpiI7O1tcd+jQIcyePVslUUtPT8e1a9fwzDPPAACuX7+OoKAgmJmZwdzcHAEBAcjIyBDLh4aGqvTk3b9/H8HBwTA0NIS1tTU+/PBDDB48uMIwx4KCAowfPx7GxsawtbXFp59+Km6zt7cHALi5uUEikWDw4MHitvXr11fZTgBw4sQJuLm5QSaToVevXkhKSqq0PR43HPqoAdpquyA7/za6KZPVHQoRERGRZvltNXDs45rLWXcHXt6kuu6bF4GsczXv6zkN8AqrX3xV2LhxIyIiIrB69Wq4ubkhKSkJkyZNgqGhIUJCQrBy5Urs3LkTW7Zsga2tLa5fv47r168DAE6ePAkLCwvExcXB19cXUqm00mP069cPOjo6SEhIQHBwMJKTk1FYWIgJEyZg1qxZSE9Ph729PRISEiCTyeDp6Qm5XA4fHx94enri8OHD0NbWxqJFi+Dr64vz589DV1e3wnFmzJiBo0ePYufOnbC0tERERATOnDlTYQhjTEwMFi5ciPfeew/fffcdXn/9dQwaNAjOzs44ceIEevfujf3796Nr167icWpqp/z8fIwYMQJDhw7F119/jfT0dLz55puN+rfSVEzUNMDel9bAd9nPeLboY5zTNwPwQN0hEREREWmG4vvA/b9rLmfaruK6glu127f4ft3jqsG8efMQExOD0aNHAyjrUUpOTsa6desQEhKCzMxMODo6on///pBIJOjYsaO4b9u2bQEAZmZmsLKyqvIYhoaGcHd3x6FDhxAcHIzExET0798fenp68PLyQmJiIuzt7ZGYmAhPT0/o6enh66+/hlKpxPr168V77OLi4mBmZobExEQMGzZM5Rj379/HF198gW+++QZDhgwRy9vY2FSIx8/PD1OnTgUAzJo1Cx9++CESEhLg7OwsnlPr1q1Vzqmmdvrmm2+gVCqxYcMGyGQydO3aFTdu3MDrr79etz9IC8RETYNMl4dBqpMGA3ym7lCIiIiINIOeMWBcMSmooLLZsg3a1G5fPeO6x1WNBw8eIC0tDRMmTMCkSZPE9aWlpTA1NQVQNrxw6NChcHZ2hq+vL0aMGFEhSaqN/v3748cffwRQdh9a+ZDCQYMGITExEa+++ioSExPFOM6dO4crV67A2Fj1nIuKipCWllah/qtXr0Iul6N3797iOlNTUzg7V5z0ztXVVXxfPgw0Jyenythr004XL16Eq6srZDKZuN3T07PKOh8nTNSIiIiISHN5hdV/WOKjQyGbSX5+PgDgs88+Q58+fVS2lQ9jdHd3R3p6Ovbs2YP9+/cjKCgI3t7e+O677+p0rAEDBiAmJgZ//fUXEhMTxQlMBg0ahHXr1iEtLQ3Xr18XJxLJz89Hz549sXHjxgp1lfd61ZfOQ88DBsqSNaVSWWX52rTTk4yJmoZo3AlQiYiIiEhdLC0tYWNjg6tXryI4OLjKciYmJhg7dizGjh2LwMBA+Pr64s6dOzA3N4eOjg4UCkWNx+rduzd0dXWxZs0aFBUVoWfPngAADw8P/PPPP/j8889haGgo9oi5u7tj8+bNsLCwgImJSY31d+rUCTo6Ojh58iRsbW0BALm5ubh8+TIGDhxYm+YAAPGetIfPqTbt5OLigq+++gpFRUVir9rvv/9e6+O2ZEzUNMCAr17C/bZ3od/KCCW3hqg7HCIiIiJqoPnz5yM8PBympqbw9fVFcXExTp06hbt372LGjBmIjY2FtbU13NzcoKWlha1bt8LKykqcFt/Ozg4HDhxAv379oKenh1atWlV6HH19ffTt2xerVq1Cv379xJ4oXV1dlfXlvV3BwcH44IMPEBAQgAULFqB9+/a4du0atm3bhnfffRft27dXqd/Y2BghISF45513YG5uDgsLC8ybNw9aWlo1PkfuYRYWFtDX18fevXvRvn17yGQymJqa1thOL7/8Mt5//31MmjQJc+bMQUZGBpYvX16Pv0jLw+n5NUABsqGll4M2eunwbPtpzTs0lZICYNdMYIOP6uvYavXFRERERNQCTZw4EevXr0dcXBy6deuGQYMGIT4+Xpym3tjYGMuWLUOvXr3g4eGBjIwM7N69G1paZT/PY2JisG/fPnTo0AFubm7VHmvw4MG4f/++ypT3QNnwx/v374vT8gOAgYEBfv31V9ja2mL06NFwcXHBhAkTUFRUVGUPW2xsLDw9PTFixAh4e3ujX79+4nT6taWtrY2VK1di3bp1sLGxQUBAQK3aycjICD/++CMuXLgANzc3vP/++1i6dGmtj9uSSYTGfuz4EyIvLw+mpqbIzc2tVbdxdVw/7w9BmotWpUrc1f4vd36t+2uY1mNaQ0OtvfNbgW0Tqy/zwhdA15HNEk5Tksvl2L17N/z8/CqMp6amw3ZXD7a7erDd1YPtrh4NbfeioiJxKvm6/Ph/0imVSuTl5cHExERM8JrDgwcP0K5dO8TExGDChAnNdtzmVN01efv2bbRp06ZR8oDqcOijBlE+0nvsZ+/XvAEU3K5+u4074ODdPLEQERERkUZISkrCpUuX0Lt3b+Tm5mLBggUAIPaKUdNgoqahQruGwt7UXn0BjP4MeHqM6jotzr5DRERE9CRavnw5UlJSoKuri549e+Lw4cNo06aSRyJQo2GipqEkqP3NmU0TgBYTMyIiIiKCm5sbTp8+re4wnjicTESDaHGSfiIiIiIiAhM1IiIiIiIijcNEjYiIiIiISMMwUSMiIiIiItIwTNQ0wFDrYHTNcYJFrq26QyEiIiIiIg3ARE0DLPGeiDN3X0VS3gh1h0JERERERBqAiRoRERERkQaxs7PDihUr1B2GxkpMTIREIsG9e/caVI+mtzOfo6YhSpQS6BpeafyK0xKAy3sBoRZT/2dfaPzjExERET2mJJLqn3s7b948REZG1rnekydPwtDQsJ5RlRk8eDAOHToEANDT04OtrS1effVVzJ49u8a4STMwUdMAh9OuorVeCkraHvhvZWP8+3lwC9j4AqCUN0JlRERERPSwrKws8f3mzZsRERGBlJQUcZ2RkZH4XhAEKBQKaGvX/PO7bdu2jRLfpEmTsGDBAhQXF+PgwYOYPHkyzMzM8PrrrzdK/dS0OPRRA7x5dAJKOsWprBvYbmDDK869Ub8kTc8UsG+E4xMRERE9xqysrMSXqakpJBKJuHzp0iUYGxtjz5496NmzJ/T09HDkyBGkpaUhICAAlpaWMDIygoeHB/bv369S76ND8iQSCdavX49Ro0bBwMAAjo6O2LlzZ43xGRgYwMrKCh07dsSrr74KV1dX7Nu3T9xeXFyMmTNnol27djA0NESfPn2QmJgobr927Rr8/f3RqlUrGBoaomvXrti9ezcAQKFQYMKECbC3t4e+vj6cnZ3x0UcfqRw/NDQUI0eOxOLFi2FpaQkzMzMsWLAApaWleOedd2Bubo727dsjLu6/38EZGRmQSCTYtGkTvLy8IJPJ8PTTT4u9g1U5cuQIBgwYAH19fXTo0AHh4eF48OCBuD0nJwf+/v7Q19eHvb09Nm7cWGP7qRt71DSQt603eln1atxKXZ4H+k+vXdm2XQDdhnW3ExERETXU2J/G4lbhrWY9Zhv9Ntg8YnOj1Td79mwsX74cnTp1QqtWrXD9+nX4+fkhKioKenp6+PLLL+Hv74+UlBTY2lY9A/j8+fOxbNkyfPDBB1i1ahWCg4ORnp5eqx46QRBw5MgRXLp0CY6OjuL6sLAwJCcnY9OmTbCxscH27dvh6+uLCxcuwNHREdOmTUNJSQl+/fVXGBoaIjk5WewlVCqVaN++PbZu3YrWrVvjt99+w+TJk2FtbY2goCDxGAcPHkT79u3x66+/4ujRo5gwYQJ+++03DBw4EMePH8fmzZsxZcoUDB06FO3btxf3e+edd7BixQo89dRTiI2Nhb+/P9LT09G6desK55eWlgZfX18sWrQIn3/+Of755x+EhYUhLCxMTAJDQ0Px999/IyEhATo6OggPD0dOTk7Nf0A1YqKmgcxl5o1fqZEF0K5n49dLRERE1ERuFd5CToFm/5iuyYIFCzB06FBx2dzcHN27dxeXFy5ciO3bt2Pnzp0ICwursp7Q0FC89NJLAIDFixdj5cqVOHHiBLy8vKrcZ82aNVi/fj1KSkogl8shk8kQHh4OAMjMzERcXBwyMzNhY2MDAJg5cyb27t2LuLg4LF68GJmZmRgzZgy6desGAOjUqZNYt46ODubPny8u29vb49ixY9iyZYtKomZubo6VK1dCS0sLzs7OWLZsGQoKCvDee+8BAObMmYMlS5bgyJEjePHFF8X9wsLCMGbMGADA2rVrsXfvXmzYsAHvvvtuhfOMjo5GcHAwpk+fDgBwdHTEypUrMWjQIKxduxaZmZnYs2cPTpw4AQ8PDwDAhg0b4OLiUmXbaQImakRERESkkdrot2nxx+zVS3WUVH5+PiIjI7Fr1y5kZWWhtLQUhYWFyMzMrLYeV1dX8b2hoSFMTExq7BEKDg7G+++/j7t372LevHnw8vISE7sLFy5AoVDAyclJZZ/i4mKx1yo8PByvv/46fvnlF3h7e2PMmDEqcXz88cf4/PPPkZmZicLCQpSUlKBHjx4q9XXt2hVaWv/dbWVpaYmnn35aXJZKpWjdunWFc/H09BTfa2tro1evXrh48WKl53nu3DmcP39eZTijIAhQKpVIT0/H5cuXoa2tjZ49/+u06NKlC8zMzKprPrVjokZEREREGqkxhyCqy6OzN86cORP79u3D8uXL4eDgAH19fQQGBqKkpKTaenR0dFSWJRIJlEpltfuYmprCwcEBALBlyxY4ODigb9++8Pb2Rn5+PqRSKU6fPg2pVKqyX/nwxokTJ8LHxwe7du3CL7/8gujoaMTExOCNN97Apk2bMHPmTMTExMDT0xPGxsb44IMPcPz48Rrjrs+5VCc/Px9TpkwRewsfZmtri8uXL9e7bnViokZERERE1EyOHj2K0NBQjBo1CkBZkpGRkdHkxzUyMsKbb76JmTNnIikpCW5ublAoFMjJycGAAQOq3K9Dhw547bXX8Nprr2HOnDn47LPP8MYbb+Do0aPw8vLC1KlTxbJpaWmNFu/vv/+OgQPLJrcrLS3F6dOnqxwa6u7ujuTkZDEpfVSXLl3EOsqHPqakpDT4OWxNjbM+EhERERE1E0dHR2zbtg1nz57FuXPn8PLLLzeoN6kupkyZgsuXL+P777+Hk5MTgoODMW7cOGzbtg3p6ek4ceIEoqOjsWvXLgDA9OnT8fPPPyM9PR1nzpxBQkKCeF+Xo6MjTp06hZ9//hmXL1/G3LlzcfLkyUaL9eOPP8b27dtx6dIlTJs2DXfv3sX48eMrLTtr1iz89ttvCAsLw9mzZ5GamooffvhBTOycnZ3h6+uLKVOm4Pjx4zh9+jQmTpwIfX39Rou3KTBRIyIiIiJqJrGxsWjVqhW8vLzg7+8PHx8fuLu7N8uxzc3NMW7cOERGRkKpVCIuLg7jxo3D22+/DWdnZ4wcORInT54UZ59UKBSYNm0aXFxc4OvrCycnJ6xZswZAWdI3evRojB07Fn369MHt27dVetcaasmSJViyZAm6d++OI0eOYOfOnWjTpvL7B11dXXHo0CFcvnwZAwYMgJubGyIiIsRJUgAgLi4ONjY2GDRoEEaPHo3JkyfDwsKi0eJtChJBEAR1B9ES5eXlwdTUFLm5uTAxMWlQXd029Ae0c8XlIKcgzPWc29AQgb/PAp8OKnvvMREYHtPwOh8Tcrkcu3fvhp+fX4Vx0tR02O7qwXZXD7a7erDd1aOh7V5UVIT09HTY29tDJpM1QYSPJ6VSiby8PJiYmKhM2NGSZWRkwN7eHklJSRUmJmlO1V2Tt2/fRps2bRolD6jO4/EXJSIiIiIieoxwMhEN8JrjEmw88gPut9tbcaMgANdPALev1L3ie9VP80pERERERJqJiZoG6GrhgDsmmah0oMDFH4EtrzR3SEREREREzc7Ozg68M6sMhz5qCInkv2dn2Jna/bfhr9ONcwDrHo1TDxERERERNTn2qGkAQQAg+W95lMOoygt6hgGtO9f9AK3sAPvBdd+PiIiIiIjUgomaBvg2eSdMtLNR8O+ylqSKjk7n5wC7/s0WFxERERERqQcTNQ1w7N6XgF6+usMgIiIiIiINwXvUNJBEIqm5EBERERERPbaYqGkgCZioERERERE9yZioERERERGRxomMjESPHj0aVEdGRgYkEgnOnj3bKDE1JyZqGohDH4mIiIg0n0QiqfYVGRnZoLp37NhRY7lWrVpBKpVCIpHAxMQEHh4e+OGHH+p9XNIcTNSIiIiIiOohKytLfK1YsQImJiYq62bOnNkscWzYsAFZWVk4deoU+vXrh8DAQFy4cKFZjk1Nh4maBuI9akRERESaz8rKSnyZmppCIpGorNu0aRNcXFwgk8nQpUsXrFmzRty3pKQEYWFhsLa2hkwmQ8eOHREdHQ0AsLOzAwCMGjUKEolEXK6KmZkZrKys4OTkhIULF6K0tBQJCQni9uvXryMoKAhmZmYwNzdHQEAAMjIyxO2JiYno3bs3DA0NYWZmhn79+uHatWsAgLS0NAQEBMDS0hJGRkbw8PDA/v37VY5vZ2eHRYsWYdy4cTAyMkLHjh2xc+dO/PPPPwgICICRkRFcXV1x6tQpcZ/4+HiYmZlhx44dcHR0hEwmg4+PD65fv17tua5fv77KNgWAEydOwM3NDTKZDL169UJSUlK19WkyTs+vgVQSNWWp+gIhIiIiUrMv/vwCXyZ/WWO5p8yfwqohq1TWvXHgDSTfSa5x33FPjUNI15B6x1iZjRs3IiIiAqtXr4abmxuSkpIwadIkGBoaIiQkBCtXrsTOnTuxZcsW2Nra4vr162KScvLkSVhYWCAuLg6+vr6QSqW1OmZpaSk2bNgAANDV1QUAyOVy+Pj4wNPTE4cPH4a2tjYWLVoEX19fnD9/HlpaWhg5ciQmTZqEb7/9FiUlJThx4oR4K05+fj78/PwQFRUFPT09fPnll/D390dKSgpsbW3FY3/44YdYvHgx5s6diw8//BCvvPIKvLy8MH78eHzwwQeYNWsWxo0bhz///FOsu6CgAFFRUfjyyy+hq6uLqVOn4sUXX8TRo0fr1ab5+fkYMWIEhg4diq+//hrp6el488036/cH1ABM1DSZohQ4tlrdURARERGpzQP5A+QU5NRYzsrQqsK6O8V3arXvA/mDesVWnXnz5iEmJgajR48GANjb2yM5ORnr1q1DSEgIMjMz4ejoiP79+0MikaBjx47ivm3btgXwX09ZTYKDgyGVSlFYWAilUgk7OzsEBQUBADZv3gylUon169eLCVJcXBzMzMyQmJiIXr16ITc3FyNGjEDnzp0BAC4uLmLd3bt3R/fu3cXlhQsXYvv27di5cyfCwsLE9X5+fpgyZQoAICIiAmvXroWHhwdeeOEFAMCsWbPg6emJmzdviuckl8uxevVq9OnTBwDwxRdfwMXFBSdOnEDv3r3r3KbffPMNlEolNmzYAJlMhq5du+LGjRt4/fXXa2xDTcRETQNIBRNIhFyUlneklf/3n4uqBU07NGdYRERERGpnqGMICwOLGsuZ65lXuq42+xrqGNYrtqo8ePAAaWlpmDBhAiZNmiSuLy0thampKQAgNDQUQ4cOhbOzM3x9fTFixAgMGzasXseLiYnBsGHDcPXqVbz11ltYuXIlzM3L2uPcuXO4cuUKjI2NVfYpKipCWloahg0bhtDQUPj4+GDo0KHw9vZGUFAQrK2tAZT1qEVGRmLXrl3IyspCaWkpCgsLkZmZqVKfq6ur+N7S0hIA0K1btwrrcnJyxERNW1sbHh4eYpkuXbrAzMwMFy9erJCo1aZNL168CFdXV8hkMnG7p6dnXZpSozBR0wAfeK5H+K9ToG2QobpBUP733sgSaNURRERERE+SkK4h9R6W+OhQyOaSn58PAPjss8/E3qJy5cMY3d3dkZ6ejj179mD//v0ICgqCt7c3vvvuuzofz8rKCg4ODnBwcEBcXBz8/PyQnJwMCwsL5Ofno2fPnti4cWOF/cp77uLi4hAeHo69e/di8+bN+N///od9+/ahb9++mDlzJvbt24fly5fDwcEB+vr6CAwMRElJiUpdOjo64vvynrvK1imVStRHbdr0ccNETWMI4rtKJxPpMqIZYyEiIiKi+rK0tISNjQ2uXr2K4ODgKsuZmJhg7NixGDt2LAIDA+Hr64s7d+7A3NwcOjo6UCgUdT5279690bNnT0RFReGjjz6Cu7s7Nm/eDAsLC5iYmFS5n5ubG9zc3DBnzhx4enrim2++Qd++fXH06FGEhoZi1KhRAMoSpocnImmI0tJSnDp1Suw9S0lJwb1791SGXparTZu6uLjgq6++QlFRkdir9vvvvzdKrOrAWR81gCCoLnPWRyIiIqKWbf78+YiOjsbKlStx+fJlXLhwAXFxcYiNjQUAxMbG4ttvv8WlS5dw+fJlbN26FVZWVjAzMwNQNpPigQMHkJ2djbt379bp2NOnT8e6devw119/ITg4GG3atEFAQAAOHz6M9PR0JCYmIjw8HDdu3EB6ejrmzJmDY8eO4dq1a/jll1+QmpoqJkuOjo7Ytm0bzp49i3PnzuHll1+ud6/Yo3R0dPDGG2/g+PHjOH36NEJDQ9G3b99K708Dam7Tl19+GRKJBJMmTUJycjJ2796N5cuXN0qs6sBETUMwNSMiIiJ6fEycOBHr169HXFwcunXrhkGDBiE+Ph729vYAAGNjYyxbtgy9evWCh4cHMjIysHv3bmhplf08j4mJwb59+9ChQwe4ubnV6di+vr6wt7dHVFQUDAwM8Ouvv8LW1hajR4+Gi4sLJkyYgKKiIpiYmMDAwACXLl3CmDFj4OTkhMmTJ2PatGnixCCxsbFo1aoVvLy84O/vDx8fH7i7uzdKGxkYGGDWrFl4+eWX0a9fPxgZGWHz5s1Vlq+pTY2MjPDjjz/iwoULcHNzw/vvv4+lS5c2SqzqIBGER/tzqDby8vJgamqK3NzcaruRa2Pw59PwAEdQJC37vxPnxp2DlkQLyDoHrBtYVqjXBGBEbEPDpn/J5XLs3r0bfn5+KuOnqWmx3dWD7a4ebHf1YLurR0PbvaioCOnp6bC3t1eZCIKqp1QqkZeXBxMTEzHBayni4+Mxffp03Lt3T92hVKq6a/L27dto06ZNo+QB1eE9ahrgtnAO0P6vC5lDH4mIiIiInmwtK/UmIiIiIiJ6AjBR00Dl05cSERERET2OQkNDNXbYo6ZgokZERERERKRhmKgRERERkUbgHHekKTThWmSipgEevgwkD18U8sJmj4WIiIiouZXPFFlQUKDmSIjKlF+L6pw9lrM+aoT/ZnwUHr4/7W7Gf+/zbzZfOERERETNSCqVwszMDDk5OQDKnq/Fe/ZrplQqUVJSgqKiohY3Pb+mEgQBBQUFyMnJgZmZGaRSqdpiYaKmYaQP96hJdf9738qu2WMhIiIiai5WVlYAICZrVDNBEFBYWAh9fX0mto3MzMxMvCbVhYmahhlSXMV4WBOb5g2EiIiIqBlJJBJYW1vDwsICcrlc3eG0CHK5HL/++isGDhzIB7w3Ih0dHbX2pJVjoqYB9IqfRon2MQCA0qS9mqMhIiIiUh+pVKoRP5JbAqlUitLSUshkMiZqjyGNHsyqUCgwd+5c2NvbQ19fH507d8bChQtVZmERBAERERGwtraGvr4+vL29kZqaWmPdH3/8Mezs7CCTydCnTx+cOHGiKU+lWs6ykeJ7hUVXtcVBRERERESaQaMTtaVLl2Lt2rVYvXo1Ll68iKVLl2LZsmVYtWqVWGbZsmVYuXIlPvnkExw/fhyGhobw8fFBUVFRlfVu3rwZM2bMwLx583DmzBl0794dPj4+ahsTrf7JP4mIiIiISJNodKL222+/ISAgAMOHD4ednR0CAwMxbNgwsfdLEASsWLEC//vf/xAQEABXV1d8+eWX+Pvvv7Fjx44q642NjcWkSZPw6quv4qmnnsInn3wCAwMDfP755810ZlXjbaBERERERKTR96h5eXnh008/xeXLl+Hk5IRz587hyJEjiI2NBQCkp6cjOzsb3t7e4j6mpqbo06cPjh07hhdffLFCnSUlJTh9+jTmzJkjrtPS0oK3tzeOHTtWZSzFxcUoLi4Wl3NzcwEAd+7cafANryUP8qHQUQAAivKLcPv2bQCAJPc+tP+dXESR9wDKf9dTw8nlchQUFOD27dsc092M2O7qwXZXD7a7erDd1YPtrh5sd/W4c+cOgKZ/KLZGJ2qzZ89GXl4eunTpAqlUCoVCgaioKAQHBwMAsrOzAQCWlpYq+1laWorbHnXr1i0oFIpK97l06VKVsURHR2P+/PkV1tvb29fpnGpyERfxKdZW3LBkFoBZjXosIiIiIiKqn9u3b8PU1LTJ6tfoRG3Lli3YuHEjvvnmG3Tt2hVnz57F9OnTYWNjg5CQkGaNZc6cOZgxY4a4rFQqcefOHbRu3brBz63Iy8tDhw4dcP36dZiYmDQ0VKoFtrl6sN3Vg+2uHmx39WC7qwfbXT3Y7uqRm5sLW1tbmJubN+lxNDpRe+eddzB79mxxCGO3bt1w7do1REdHIyQkRHwI3c2bN2FtbS3ud/PmTfTo0aPSOtu0aQOpVIqbN2+qrL9582a1D7XT09ODnp6eyjozM7N6nFXVTExM+I+smbHN1YPtrh5sd/Vgu6sH21092O7qwXZXDy2tpp3uQ6MnEykoKKjQAFKpFEqlEkDZsEMrKyscOHBA3J6Xl4fjx4/D09Oz0jp1dXXRs2dPlX2USiUOHDhQ5T5ERERERETNSaN71Pz9/REVFQVbW1t07doVSUlJiI2Nxfjx4wGUPcF++vTpWLRoERwdHWFvb4+5c+fCxsYGI0eOFOsZMmQIRo0ahbCwMADAjBkzEBISgl69eqF3795YsWIFHjx4gFdffVUdp0lERERERKRCoxO1VatWYe7cuZg6dSpycnJgY2ODKVOmICIiQizz7rvv4sGDB5g8eTLu3buH/v37Y+/evZDJZGKZtLQ03Lp1S1weO3Ys/vnnH0RERCA7Oxs9evTA3r17K0ww0lz09PQwb968CkMrqemwzdWD7a4ebHf1YLurB9tdPdju6sF2V4/maneJ0NTzShIREREREVGdaPQ9akRERERERE8iJmpEREREREQahokaERERERGRhmGiRkREREREpGGYqDWDjz/+GHZ2dpDJZOjTpw9OnDhRbfmtW7eiS5cukMlk6NatG3bv3t1MkT4+oqOj4eHhAWNjY1hYWGDkyJFISUmpdp/4+HhIJBKV18Ozh1L1IiMjK7Rfly5dqt2H13rD2dnZVWh3iUSCadOmVVqe13n9/Prrr/D394eNjQ0kEgl27Nihsl0QBERERMDa2hr6+vrw9vZGampqjfXW9fvhSVNdu8vlcsyaNQvdunWDoaEhbGxsMG7cOPz999/V1lmfz6onTU3Xe2hoaIU29PX1rbFeXu/Vq6ndK/usl0gk+OCDD6qsk9d79Wrze7GoqAjTpk1D69atYWRkhDFjxuDmzZvV1lvf74RHMVFrYps3b8aMGTMwb948nDlzBt27d4ePjw9ycnIqLf/bb7/hpZdewoQJE5CUlISRI0di5MiR+OOPP5o58pbt0KFDmDZtGn7//Xfs27cPcrkcw4YNw4MHD6rdz8TEBFlZWeLr2rVrzRTx46Fr164q7XfkyJEqy/JabxwnT55UafN9+/YBAF544YUq9+F1XncPHjxA9+7d8fHHH1e6fdmyZVi5ciU++eQTHD9+HIaGhvDx8UFRUVGVddb1++FJVF27FxQU4MyZM5g7dy7OnDmDbdu2ISUlBc8//3yN9dbls+pJVNP1DgC+vr4qbfjtt99WWyev95rV1O4Pt3dWVhY+//xzSCQSjBkzptp6eb1XrTa/F9966y38+OOP2Lp1Kw4dOoS///4bo0ePrrbe+nwnVEqgJtW7d29h2rRp4rJCoRBsbGyE6OjoSssHBQUJw4cPV1nXp08fYcqUKU0a5+MuJydHACAcOnSoyjJxcXGCqalp8wX1mJk3b57QvXv3Wpfntd403nzzTaFz586CUqmsdDuv84YDIGzfvl1cViqVgpWVlfDBBx+I6+7duyfo6ekJ3377bZX11PX74Un3aLtX5sSJEwIA4dq1a1WWqetn1ZOusnYPCQkRAgIC6lQPr/e6qc31HhAQIDz77LPVluH1XjeP/l68d++eoKOjI2zdulUsc/HiRQGAcOzYsUrrqO93QmXYo9aESkpKcPr0aXh7e4vrtLS04O3tjWPHjlW6z7Fjx1TKA4CPj0+V5al2cnNzAQDm5ubVlsvPz0fHjh3RoUMHBAQE4M8//2yO8B4bqampsLGxQadOnRAcHIzMzMwqy/Jab3wlJSX4+uuvMX78eEgkkirL8TpvXOnp6cjOzla5nk1NTdGnT58qr+f6fD9QzXJzcyGRSGBmZlZtubp8VlHlEhMTYWFhAWdnZ7z++uu4fft2lWV5vTe+mzdvYteuXZgwYUKNZXm9196jvxdPnz4NuVyucu126dIFtra2VV679flOqAoTtSZ069YtKBQKWFpaqqy3tLREdnZ2pftkZ2fXqTzVTKlUYvr06ejXrx+efvrpKss5Ozvj888/xw8//ICvv/4aSqUSXl5euHHjRjNG23L16dMH8fHx2Lt3L9auXYv09HQMGDAA9+/fr7Q8r/XGt2PHDty7dw+hoaFVluF13vjKr9m6XM/1+X6g6hUVFWHWrFl46aWXYGJiUmW5un5WUUW+vr748ssvceDAASxduhSHDh3Cc889B4VCUWl5Xu+N74svvoCxsXGNQ/B4vddeZb8Xs7OzoaurW+F//tT0W768TG33qYp2nUoTtUDTpk3DH3/8UeOYbE9PT3h6eorLXl5ecHFxwbp167Bw4cKmDrPFe+6558T3rq6u6NOnDzp27IgtW7bU6v/4UcNt2LABzz33HGxsbKosw+ucHkdyuRxBQUEQBAFr166ttiw/qxruxRdfFN9369YNrq6u6Ny5MxITEzFkyBA1Rvbk+PzzzxEcHFzjZFC83muvtr8XmxN71JpQmzZtIJVKK8wMc/PmTVhZWVW6j5WVVZ3KU/XCwsLw008/ISEhAe3bt6/Tvjo6OnBzc8OVK1eaKLrHm5mZGZycnKpsP17rjevatWvYv38/Jk6cWKf9eJ03XPk1W5fruT7fD1S58iTt2rVr2LdvX7W9aZWp6bOKatapUye0adOmyjbk9d64Dh8+jJSUlDp/3gO83qtS1e9FKysrlJSU4N69eyrla/otX16mtvtUhYlaE9LV1UXPnj1x4MABcZ1SqcSBAwdU/o/2wzw9PVXKA8C+ffuqLE+VEwQBYWFh2L59Ow4ePAh7e/s616FQKHDhwgVYW1s3QYSPv/z8fKSlpVXZfrzWG1dcXBwsLCwwfPjwOu3H67zh7O3tYWVlpXI95+Xl4fjx41Vez/X5fqCKypO01NRU7N+/H61bt65zHTV9VlHNbty4gdu3b1fZhrzeG9eGDRvQs2dPdO/evc778npXVdPvxZ49e0JHR0fl2k1JSUFmZmaV1259vhOqC5Ca0KZNmwQ9PT0hPj5eSE5OFiZPniyYmZkJ2dnZgiAIwiuvvCLMnj1bLH/06FFBW1tbWL58uXDx4kVh3rx5go6OjnDhwgV1nUKL9PrrrwumpqZCYmKikJWVJb4KCgrEMo+2/fz584Wff/5ZSEtLE06fPi28+OKLgkwmE/788091nEKL8/bbbwuJiYlCenq6cPToUcHb21to06aNkJOTIwgCr/WmpFAoBFtbW2HWrFkVtvE6bxz3798XkpKShKSkJAGAEBsbKyQlJYmzCy5ZskQwMzMTfvjhB+H8+fNCQECAYG9vLxQWFop1PPvss8KqVavE5Zq+H6j6di8pKRGef/55oX379sLZs2dVPuuLi4vFOh5t95o+q6j6dr9//74wc+ZM4dixY0J6erqwf/9+wd3dXXB0dBSKiorEOni9111NnzOCIAi5ubmCgYGBsHbt2krr4PVeN7X5vfjaa68Jtra2wsGDB4VTp04Jnp6egqenp0o9zs7OwrZt28Tl2nwn1AYTtWawatUqwdbWVtDV1RV69+4t/P777+K2QYMGCSEhISrlt2zZIjg5OQm6urpC165dhV27djVzxC0fgEpfcXFxYplH23769Oni38nS0lLw8/MTzpw50/zBt1Bjx44VrK2tBV1dXaFdu3bC2LFjhStXrojbea03nZ9//lkAIKSkpFTYxuu8cSQkJFT6mVLetkqlUpg7d65gaWkp6OnpCUOGDKnw9+jYsaMwb948lXXVfT9Q9e2enp5e5Wd9QkKCWMej7V7TZxVV3+4FBQXCsGHDhLZt2wo6OjpCx44dhUmTJlVIuHi9111NnzOCIAjr1q0T9PX1hXv37lVaB6/3uqnN78XCwkJh6tSpQqtWrQQDAwNh1KhRQlZWVoV6Ht6nNt8JtSH5t3IiIiIiIiLSELxHjYiIiIiISMMwUSMiIiIiItIwTNSIiIiIiIg0DBM1IiIiIiIiDcNEjYiIiIiISMMwUSMiIiIiItIwTNSIiIiIiIg0DBM1IiJqdvHx8TAzM1N3GA0ikUiwY8eOasuEhoZi5MiRzRJPZSIjIyGRSCCRSLBixYoG1TV48GCxrrNnzzZKfEREVDUmakREVC+hoaHiD/eHX1euXFF3aM0iKysLzz33HAAgIyOj0gTmo48+Qnx8fPMH95CuXbsiKysLkydPFtfNmDED5ubm6NChAzZu3KhSfuvWrfD3969Qz7Zt23DixIkmj5eIiMpoqzsAIiJquXx9fREXF6eyrm3btmqKpnlZWVnVWMbU1LQZIqmetra2Sqw//vgjvvnmG/zyyy9ITU3F+PHj4ePjgzZt2iA3Nxfvv/8+9u/fX6Eec3Nz5OXlNWfoRERPNPaoERFRvenp6cHKykrlJZVKERsbi27dusHQ0BAdOnTA1KlTkZ+fX2U9586dwzPPPANjY2OYmJigZ8+eOHXqlLj9yJEjGDBgAPT19dGhQweEh4fjwYMHVdYXGRmJHj16YN26dejQoQMMDAwQFBSE3NxcsYxSqcSCBQvQvn176OnpoUePHti7d6+4vaSkBGFhYbC2toZMJkPHjh0RHR0tbn946KO9vT0AwM3NDRKJBIMHDwagOvTx008/hY2NDZRKpUqsAQEBGD9+vLj8ww8/wN3dHTKZDJ06dcL8+fNRWloKABAEAZGRkbC1tYWenh5sbGwQHh5eZTtU5uLFixg8eDB69eqFl156CSYmJkhPTwcAvPvuu3j99ddha2tbpzqJiKjxMVEjIqJGp6WlhZUrV+LPP//EF198gYMHD+Ldd9+tsnxwcDDat2+PkydP4vTp05g9ezZ0dHQAAGlpafD19cWYMWNw/vx5bN68GUeOHEFYWFi1MVy5cgVbtmzBjz/+iL179yIpKQlTp04Vt3/00UeIiYnB8uXLcf78efj4+OD5559HamoqAGDlypXYuXMntmzZgpSUFGzcuBF2dnaVHqt8SOD+/fuRlZWFbdu2VSjzwgsv4Pbt20hISBDX3blzB3v37kVwcDAA4PDhwxg3bhzefPNNJCcnY926dYiPj0dUVBQA4Pvvv8eHH36IdevWITU1FTt27EC3bt2qbYdHde/eHadOncLdu3dx+vRpFBYWwsHBAUeOHMGZM2fqnPgREVETEYiIiOohJCREkEqlgqGhofgKDAystOzWrVuF1q1bi8txcXGCqampuGxsbCzEx8dXuu+ECROEyZMnq6w7fPiwoKWlJRQWFla6z7x58wSpVCrcuHFDXLdnzx5BS0tLyMrKEgRBEGxsbISoqCiV/Tw8PISpU6cKgiAIb7zxhvDss88KSqWy0mMAELZv3y4IgiCkp6cLAISkpCSVMiEhIUJAQIC4HBAQIIwfP15cXrdunWBjYyMoFApBEARhyJAhwuLFi1Xq+OqrrwRra2tBEAQhJiZGcHJyEkpKSiqNqbJ26N69e6XrO3fuLDz99NPCtm3bhOLiYuHpp58WTp06JaxatUpwcnISvLy8hD/++ENlv6rOk4iIGh971IiIqN6eeeYZnD17VnytXLkSQFnP0pAhQ9CuXTsYGxvjlVdewe3bt1FQUFBpPTNmzMDEiRPh7e2NJUuWIC0tTdx27tw5xMfHw8jISHz5+PhAqVSKQ/YqY2tri3bt2onLnp6eUCqVSElJQV5eHv7++2/069dPZZ9+/frh4sWLAMqGLZ49exbOzs4IDw/HL7/8Uu92KhccHIzvv/8excXFAICNGzfixRdfhJaWlniuCxYsUDnXSZMmISsrCwUFBXjhhRdQWFiITp06YdKkSdi+fbs4LLIuIiMjceXKFVy4cAGjRo1CdHQ0vL29oaOjg0WLFuHIkSOYOHEixo0b1+BzJiKi+mGiRkRE9WZoaAgHBwfxZW1tjYyMDIwYMQKurq74/vvvcfr0aXz88ccAyu77qkxkZCT+/PNPDB8+HAcPHsRTTz2F7du3AwDy8/MxZcoUlYTw3LlzSE1NRefOnZvs3Nzd3ZGeno6FCxeisLAQQUFBCAwMbFCd/v7+EAQBu3btwvXr13H48GFx2CNQdq7z589XOdcLFy4gNTUVMpkMHTp0QEpKCtasWQN9fX1MnToVAwcOhFwur3dMly5dwtdff42FCxciMTERAwcORNu2bREUFIQzZ87g/v37DTpnIiKqH876SEREjer06dNQKpWIiYkRe4q2bNlS435OTk5wcnLCW2+9hZdeeglxcXEYNWoU3N3dkZycDAcHhzrFkZmZib///hs2NjYAgN9//x1aWlpwdnaGiYkJbGxscPToUQwaNEjc5+jRo+jdu7e4bGJigrFjx2Ls2LEIDAyEr68v7ty5A3Nzc5Vj6erqAgAUCkW1MclkMowePRobN27ElStX4OzsDHd3d3G7u7s7UlJSqj1XfX19+Pv7w9/fH9OmTUOXLl1w4cIFlXpqSxAETJkyBbGxsTAyMoJCoRCTvvL/1nRORETUNJioERFRo3JwcIBcLseqVavg7++Po0eP4pNPPqmyfGFhId555x0EBgbC3t4eN27cwMmTJzFmzBgAwKxZs9C3b1+EhYVh4sSJMDQ0RHJyMvbt24fVq1dXWa9MJkNISAiWL1+OvLw8hIeHIygoSJyq/p133sG8efPQuXNn9OjRA3FxcTh79qz4XLHY2FhYW1vDzc0NWlpa2Lp1K6ysrCp9ULeFhQX09fWxd+9etG/fHjKZrMqp+YODgzFixAj8+eef+L//+z+VbRERERgxYgRsbW0RGBgILS0tnDt3Dn/88QcWLVqE+Ph4KBQK9OnTBwYGBvj666+hr6+Pjh07Vvs3qcr69evRtm1b8blp/fr1Q2RkJH7//Xfs2bMHTz31VIt/MDkRUUvFRI2IiBpV9+7dERsbi6VLl2LOnDkYOHAgoqOjq7zfSSqV4vbt2xg3bhxu3ryJNm3aYPTo0Zg/fz4AwNXVFYcOHcL777+PAQMGQBAEdO7cGWPHjq02DgcHB4wePRp+fn64c+cORowYgTVr1ojbw8PDkZubi7fffhs5OTl46qmnsHPnTjg6OgIAjI2NsWzZMqSmpkIqlcLDwwO7d+8Wewkfpq2tjZUrV2LBggWIiIjAgAEDkJiYWGlczz77LMzNzZGSkoKXX35ZZZuPjw9++uknLFiwAEuXLoWOjg66dOmCiRMnAgDMzMywZMkSzJgxAwqFAt26dcOPP/6I1q1bV9sWlbl58yaioqLw22+/iet69+6Nt99+G8OHD4eFhQW++OKLOtdLRESNQyIIgqDuIIiIiBpTZGQkduzYgbNnz6o7FLVq7HbIyMiAvb09kpKS0KNHj0apk4iIKsfJRIiIiB5jFy5cgJGRkUpvYn0899xz6Nq1ayNFRURENeHQRyIiosdUeHi4eB9c27ZtG1TX+vXrUVhYCKDs0QdERNS0OPSRiIiIiIhIw3DoIxERERERkYZhokZERERERKRhmKgRERERERFpGCZqREREREREGoaJGhERERERkYZhokZERERERKRhmKgRERERERFpGCZqREREREREGoaJGhERERERkYb5f5pu7U4NQtF6AAAAAElFTkSuQmCC",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_roc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
"plot_roc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
"plot_roc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
"plot_roc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
"plot_roc(\"Train Resampled\", train_labels, train_predictions_resampled, color=colors[2])\n",
"plot_roc(\"Test Resampled\", test_labels, test_predictions_resampled, color=colors[2], linestyle='--')\n",
"plt.legend(loc='lower right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "vayGnv0VOe_v"
},
"source": [
"### Plot the AUPRC\n"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"execution": {
"iopub.execute_input": "2024-08-20T01:27:04.385054Z",
"iopub.status.busy": "2024-08-20T01:27:04.384504Z",
"iopub.status.idle": "2024-08-20T01:27:04.778240Z",
"shell.execute_reply": "2024-08-20T01:27:04.777513Z"
},
"id": "wgWXQ8aeOhCZ"
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_prc(\"Train Baseline\", train_labels, train_predictions_baseline, color=colors[0])\n",
"plot_prc(\"Test Baseline\", test_labels, test_predictions_baseline, color=colors[0], linestyle='--')\n",
"\n",
"plot_prc(\"Train Weighted\", train_labels, train_predictions_weighted, color=colors[1])\n",
"plot_prc(\"Test Weighted\", test_labels, test_predictions_weighted, color=colors[1], linestyle='--')\n",
"\n",
"plot_prc(\"Train Resampled\", train_labels, train_predictions_resampled, color=colors[2])\n",
"plot_prc(\"Test Resampled\", test_labels, test_predictions_resampled, color=colors[2], linestyle='--')\n",
"plt.legend(loc='lower right');"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3o3f0ywl8uqW"
},
"source": [
"## Applying this tutorial to your problem\n",
"\n",
"Imbalanced data classification is an inherently difficult task since there are so few samples to learn from. You should always start with the data first and do your best to collect as many samples as possible and give substantial thought to what features may be relevant so the model can get the most out of your minority class. At some point your model may struggle to improve and yield the results you want, so it is important to keep in mind the context of your problem and the trade offs between different types of errors."
]
}
],
"metadata": {
"colab": {
"name": "imbalanced_data.ipynb",
"toc_visible": true
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.19"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
![](\"https://www.tensorflow.org/images/tf_logo_32px.png\"){kind=logo}
View on TensorFlow.org\n",
" ![](\"https://www.tensorflow.org/images/colab_logo_32px.png\"){kind=logo}
Run in Google Colab\n",
" ![](\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\")
View source on GitHub\n",
" ![](\"https://www.tensorflow.org/images/download_logo_32px.png\"){kind=logo}
Download notebook\n",
"