public static final class ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig extends GeneratedMessageV3 implements ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfigOrBuilder
The config for Training & Prediction data skew detection. It specifies the
training dataset sources and the skew detection parameters.
Protobuf type
google.cloud.aiplatform.v1.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig
Static Fields
public static final int ATTRIBUTION_SCORE_SKEW_THRESHOLDS_FIELD_NUMBER
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public static final int SKEW_THRESHOLDS_FIELD_NUMBER
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Static Methods
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstance()
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public static final Descriptors.Descriptor getDescriptor()
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilder()
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilder(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig prototype)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseDelimitedFrom(InputStream input)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(byte[] data)
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| Name | Description |
| data | byte[]
|
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteString data)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(CodedInputStream input)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(InputStream input)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteBuffer data)
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
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public static Parser<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig> parser()
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Methods
public boolean containsAttributionScoreSkewThresholds(String key)
Key is the feature name and value is the threshold. The threshold here is
against attribution score distance between the training and prediction
feature.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;
public boolean containsSkewThresholds(String key)
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.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;
public boolean equals(Object obj)
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public Map<String,ThresholdConfig> getAttributionScoreSkewThresholds()
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public int getAttributionScoreSkewThresholdsCount()
Key is the feature name and value is the threshold. The threshold here is
against attribution score distance between the training and prediction
feature.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;
public Map<String,ThresholdConfig> getAttributionScoreSkewThresholdsMap()
Key is the feature name and value is the threshold. The threshold here is
against attribution score distance between the training and prediction
feature.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;
public ThresholdConfig getAttributionScoreSkewThresholdsOrDefault(String key, ThresholdConfig defaultValue)
Key is the feature name and value is the threshold. The threshold here is
against attribution score distance between the training and prediction
feature.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;
public ThresholdConfig getAttributionScoreSkewThresholdsOrThrow(String key)
Key is the feature name and value is the threshold. The threshold here is
against attribution score distance between the training and prediction
feature.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> attribution_score_skew_thresholds = 2;
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstanceForType()
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public Parser<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig> getParserForType()
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public int getSerializedSize()
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public Map<String,ThresholdConfig> getSkewThresholds()
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public int getSkewThresholdsCount()
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.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;
public Map<String,ThresholdConfig> getSkewThresholdsMap()
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.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;
public ThresholdConfig getSkewThresholdsOrDefault(String key, ThresholdConfig defaultValue)
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.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;
public ThresholdConfig getSkewThresholdsOrThrow(String key)
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.
map<string, .google.cloud.aiplatform.v1.ThresholdConfig> skew_thresholds = 1;
public final UnknownFieldSet getUnknownFields()
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protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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protected MapField internalGetMapField(int number)
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public final boolean isInitialized()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilderForType()
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protected ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
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protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder toBuilder()
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public void writeTo(CodedOutputStream output)
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