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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.
#default_skew_threshold
def default_skew_threshold() -> ::Google::Cloud::AIPlatform::V1::ThresholdConfig
Returns
- (::Google::Cloud::AIPlatform::V1::ThresholdConfig) — Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
#default_skew_threshold=
def default_skew_threshold=(value) -> ::Google::Cloud::AIPlatform::V1::ThresholdConfig
Parameter
- value (::Google::Cloud::AIPlatform::V1::ThresholdConfig) — Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
Returns
- (::Google::Cloud::AIPlatform::V1::ThresholdConfig) — Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
#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.