Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ModelMonitoringObjectiveConfig::TrainingPredictionSkewDetectionConfig (v0.3.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ModelMonitoringObjectiveConfig::TrainingPredictionSkewDetectionConfig.

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

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#attribution_score_skew_thresholds

def attribution_score_skew_thresholds() -> ::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}
Returns
  • (::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}) — Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

#attribution_score_skew_thresholds=

def attribution_score_skew_thresholds=(value) -> ::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}
Parameter
  • value (::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}) — Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
Returns
  • (::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}) — Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

#skew_thresholds

def skew_thresholds() -> ::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}
Returns
  • (::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}) — Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.

#skew_thresholds=

def skew_thresholds=(value) -> ::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}
Parameter
  • value (::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}) — Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
Returns
  • (::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ThresholdConfig}) — Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.