Class ModelMonitoringObjectiveConfig (1.0.1)

  ModelMonitoringObjectiveConfig 
 ( 
 mapping 
 = 
 None 
 , 
 * 
 , 
 ignore_unknown_fields 
 = 
 False 
 , 
 ** 
 kwargs 
 )

Next ID: 6 .. attribute:: training_dataset

Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.

:type: google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset

Attributes

Name	Description
training_prediction_skew_detection_config	`google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig` The config for skew between training data and prediction data.
prediction_drift_detection_config	`google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.PredictionDriftDetectionConfig` The config for drift of prediction data.

Inheritance

builtins.object > proto.message.Message > ModelMonitoringObjectiveConfig

Classes

PredictionDriftDetectionConfig

  PredictionDriftDetectionConfig 
 ( 
 mapping 
 = 
 None 
 , 
 * 
 , 
 ignore_unknown_fields 
 = 
 False 
 , 
 ** 
 kwargs 
 )

The config for Prediction data drift detection. .. attribute:: drift_thresholds

Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configed for that feature. The threshold here is against feature distribution distance between different time windws.

:type: Sequence[ google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.PredictionDriftDetectionConfig.DriftThresholdsEntry ]

TrainingDataset

  TrainingDataset 
 ( 
 mapping 
 = 
 None 
 , 
 * 
 , 
 ignore_unknown_fields 
 = 
 False 
 , 
 ** 
 kwargs 
 )

Training Dataset information. .. attribute:: dataset

The resource name of the Dataset used to train this Model.

:type: str

TrainingPredictionSkewDetectionConfig

  TrainingPredictionSkewDetectionConfig 
 ( 
 mapping 
 = 
 None 
 , 
 * 
 , 
 ignore_unknown_fields 
 = 
 False 
 , 
 ** 
 kwargs 
 )

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.