Google Cloud Ai Platform V1 Client - Class TrainingPredictionSkewDetectionConfig (0.10.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class TrainingPredictionSkewDetectionConfig.

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

Generated from protobuf message google.cloud.aiplatform.v1.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Methods

__construct

Constructor.

Parameters
NameDescription
data array

Optional. Data for populating the Message object.

↳ skew_thresholds array|Google\Protobuf\Internal\MapField

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.

↳ attribution_score_skew_thresholds array|Google\Protobuf\Internal\MapField

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 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.

getSkewThresholds

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.

Generated from protobuf field map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;

Returns
TypeDescription
Google\Protobuf\Internal\MapField

setSkewThresholds

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.

Generated from protobuf field map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;

Parameter
NameDescription
var array|Google\Protobuf\Internal\MapField
Returns
TypeDescription
$this

getAttributionScoreSkewThresholds

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

Generated from protobuf field map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Returns
TypeDescription
Google\Protobuf\Internal\MapField

setAttributionScoreSkewThresholds

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

Generated from protobuf field map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Parameter
NameDescription
var array|Google\Protobuf\Internal\MapField
Returns
TypeDescription
$this

getDefaultSkewThreshold

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.

Generated from protobuf field .google.cloud.aiplatform.v1.ThresholdConfig default_skew_threshold = 6;

Returns
TypeDescription
Google\Cloud\AIPlatform\V1\ThresholdConfig|null

hasDefaultSkewThreshold

clearDefaultSkewThreshold

setDefaultSkewThreshold

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.

Generated from protobuf field .google.cloud.aiplatform.v1.ThresholdConfig default_skew_threshold = 6;

Parameter
NameDescription
var Google\Cloud\AIPlatform\V1\ThresholdConfig
Returns
TypeDescription
$this