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.v1beta1.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig
Methods
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig build()
Returns
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig buildPartial()
Returns
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clear()
Returns
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearAttributionScoreSkewThresholds()
Returns
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Returns
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Returns
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearSkewThresholds()
Returns
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clone()
Returns
Overrides
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.v1beta1.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.v1beta1.ThresholdConfig> skew_thresholds = 1;
public Map<String,ThresholdConfig> getAttributionScoreSkewThresholds()
Returns
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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.ThresholdConfig> attribution_score_skew_thresholds = 2;
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstanceForType()
Returns
public static final Descriptors.Descriptor getDescriptor()
Returns
public Descriptors.Descriptor getDescriptorForType()
Returns
Overrides
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()
Returns
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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.ThresholdConfig> skew_thresholds = 1;
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Overrides
protected MapField internalGetMapField(int number)
Parameter
Returns
Overrides
protected MapField internalGetMutableMapField(int number)
Parameter
Returns
Overrides
public final boolean isInitialized()
Returns
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig other)
Parameter
Returns
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Overrides
Exceptions
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(Message other)
Parameter
Returns
Overrides
public final ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.ThresholdConfig> skew_thresholds = 1;
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Returns
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Returns
Overrides
public final ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Returns
Overrides
