pulumi-azure-native-kotlin/com.pulumi.azurenative.machinelearningservices.kotlin.outputs/RegressionResponse

RegressionResponse

data class RegressionResponse(val cvSplitColumnNames: List<String>? = null, val featurizationSettings: TableVerticalFeaturizationSettingsResponse? = null, val limitSettings: TableVerticalLimitSettingsResponse? = null, val logVerbosity: String? = null, val nCrossValidations: Either<AutoNCrossValidationsResponse, CustomNCrossValidationsResponse>? = null, val primaryMetric: String? = null, val targetColumnName: String? = null, val taskType: String, val testData: MLTableJobInputResponse? = null, val testDataSize: Double? = null, val trainingData: MLTableJobInputResponse, val trainingSettings: RegressionTrainingSettingsResponse? = null, val validationData: MLTableJobInputResponse? = null, val validationDataSize: Double? = null, val weightColumnName: String? = null)

Regression task in AutoML Table vertical.

Constructors

RegressionResponse

constructor(cvSplitColumnNames: List<String>? = null, featurizationSettings: TableVerticalFeaturizationSettingsResponse? = null, limitSettings: TableVerticalLimitSettingsResponse? = null, logVerbosity: String? = null, nCrossValidations: Either<AutoNCrossValidationsResponse, CustomNCrossValidationsResponse>? = null, primaryMetric: String? = null, targetColumnName: String? = null, taskType: String, testData: MLTableJobInputResponse? = null, testDataSize: Double? = null, trainingData: MLTableJobInputResponse, trainingSettings: RegressionTrainingSettingsResponse? = null, validationData: MLTableJobInputResponse? = null, validationDataSize: Double? = null, weightColumnName: String? = null)

Types

object Companion

Properties

cvSplitColumnNames

val cvSplitColumnNames: List<String>? = null

Columns to use for CVSplit data.

featurizationSettings

val featurizationSettings: TableVerticalFeaturizationSettingsResponse? = null

Featurization inputs needed for AutoML job.

val limitSettings: TableVerticalLimitSettingsResponse? = null

Execution constraints for AutoMLJob.

val logVerbosity: String? = null

Log verbosity for the job.

nCrossValidations

val nCrossValidations: Either<AutoNCrossValidationsResponse, CustomNCrossValidationsResponse>? = null

Number of cross validation folds to be applied on training dataset when validation dataset is not provided.

val primaryMetric: String? = null

Primary metric for regression task.

targetColumnName

val targetColumnName: String? = null

Target column name: This is prediction values column. Also known as label column name in context of classification tasks.

val taskType: String

AutoMLJob Task type. Expected value is 'Regression'.

val testData: MLTableJobInputResponse? = null

Test data input.

val testDataSize: Double? = null

The fraction of test dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided.

val trainingData: MLTableJobInputResponse

Required Training data input.

trainingSettings

val trainingSettings: RegressionTrainingSettingsResponse? = null

Inputs for training phase for an AutoML Job.

val validationData: MLTableJobInputResponse? = null

Validation data inputs.

validationDataSize

val validationDataSize: Double? = null

The fraction of training dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided.

weightColumnName

val weightColumnName: String? = null

The name of the sample weight column. Automated ML supports a weighted column as an input, causing rows in the data to be weighted up or down.