GetModelResult

data class GetModelResult(val createTime: String, val dataState: String, val displayName: String, val filteringOption: String, val lastTuneTime: String, val modelFeaturesConfig: GoogleCloudRetailV2ModelModelFeaturesConfigResponse, val name: String, val optimizationObjective: String, val periodicTuningState: String, val servingConfigLists: List<GoogleCloudRetailV2ModelServingConfigListResponse>, val servingState: String, val trainingState: String, val tuningOperation: String, val type: String, val updateTime: String)

Constructors

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fun GetModelResult(createTime: String, dataState: String, displayName: String, filteringOption: String, lastTuneTime: String, modelFeaturesConfig: GoogleCloudRetailV2ModelModelFeaturesConfigResponse, name: String, optimizationObjective: String, periodicTuningState: String, servingConfigLists: List<GoogleCloudRetailV2ModelServingConfigListResponse>, servingState: String, trainingState: String, tuningOperation: String, type: String, updateTime: String)

Types

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object Companion

Properties

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Timestamp the Recommendation Model was created at.

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The state of data requirements for this model: DATA_OK and DATA_ERROR. Recommendation model cannot be trained if the data is in DATA_ERROR state. Recommendation model can have DATA_ERROR state even if serving state is ACTIVE: models were trained successfully before, but cannot be refreshed because model no longer has sufficient data for training.

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The display name of the model. Should be human readable, used to display Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024 characters.

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Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

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The timestamp when the latest successful tune finished.

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Optional. Additional model features config.

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The fully qualified resource name of the model. Format: projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id} catalog_id has char limit of 50. recommendation_model_id has char limit of 40.

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Optional. The optimization objective e.g. cvr. Currently supported values: ctr, cvr, revenue-per-order. If not specified, we choose default based on model type. Default depends on type of recommendation: recommended-for-you =>ctr others-you-may-like =>ctr frequently-bought-together =>revenue_per_order This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.

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Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune earlier use the TuneModel method. Default value is PERIODIC_TUNING_ENABLED.

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The list of valid serving configs associated with the PageOptimizationConfig.

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The serving state of the model: ACTIVE, NOT_ACTIVE.

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Optional. The training state that the model is in (e.g. TRAINING or PAUSED). Since part of the cost of running the service is frequency of training - this can be used to determine when to train model in order to control cost. If not specified: the default value for CreateModel method is TRAINING. The default value for UpdateModel method is to keep the state the same as before.

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The tune operation associated with the model. Can be used to determine if there is an ongoing tune for this recommendation. Empty field implies no tune is goig on.

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The type of model e.g. home-page. Currently supported values: recommended-for-you, others-you-may-like, frequently-bought-together, page-optimization, similar-items, buy-it-again, on-sale-items, and recently-viewed(readonly value). This field together with optimization_objective describe model metadata to use to control model training and serving. See https://cloud.google.com/retail/docs/models for more details on what the model metadata control and which combination of parameters are valid. For invalid combinations of parameters (e.g. type = frequently-bought-together and optimization_objective = ctr), you receive an error 400 if you try to create/update a recommendation with this set of knobs.

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Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.