public static final class ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder extends GeneratedMessageV3.Builder<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder> 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
Methods
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig build()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig buildPartial()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clear()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearAttributionScoreSkewThresholds()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearField(Descriptors.FieldDescriptor field)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearSkewThresholds()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clone()
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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 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 static final Descriptors.Descriptor getDescriptor()
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public Descriptors.Descriptor getDescriptorForType()
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public Map<String,ThresholdConfig> getMutableAttributionScoreSkewThresholds()
Use alternate mutation accessors instead.
public Map<String,ThresholdConfig> getMutableSkewThresholds()
Use alternate mutation accessors instead.
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;
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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protected MapField internalGetMapField(int number)
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protected MapField internalGetMutableMapField(int number)
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public final boolean isInitialized()
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig other)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(Message other)
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public final ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder putAllAttributionScoreSkewThresholds(Map<String,ThresholdConfig> values)
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.Builder putAllSkewThresholds(Map<String,ThresholdConfig> values)
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 ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder putAttributionScoreSkewThresholds(String key, ThresholdConfig value)
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.Builder putSkewThresholds(String key, ThresholdConfig value)
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 ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder removeAttributionScoreSkewThresholds(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.Builder removeSkewThresholds(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 ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
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public final ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
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