Class ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder (2.4.0)

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

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

build()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig build()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

buildPartial()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig buildPartial()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

clear()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clear()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

clearAttributionScoreSkewThresholds()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearAttributionScoreSkewThresholds()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

clearField(Descriptors.FieldDescriptor field)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

clearOneof(Descriptors.OneofDescriptor oneof)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

clearSkewThresholds()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clearSkewThresholds()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

clone()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder clone()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

containsAttributionScoreSkewThresholds(String key)

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;

Parameter
NameDescription
keyString
Returns
TypeDescription
boolean

containsSkewThresholds(String key)

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;

Parameter
NameDescription
keyString
Returns
TypeDescription
boolean

getAttributionScoreSkewThresholds()

public Map<String,ThresholdConfig> getAttributionScoreSkewThresholds()
Returns
TypeDescription
Map<String,ThresholdConfig>

getAttributionScoreSkewThresholdsCount()

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;

Returns
TypeDescription
int

getAttributionScoreSkewThresholdsMap()

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;

Returns
TypeDescription
Map<String,ThresholdConfig>

getAttributionScoreSkewThresholdsOrDefault(String key, ThresholdConfig defaultValue)

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;

Parameters
NameDescription
keyString
defaultValueThresholdConfig
Returns
TypeDescription
ThresholdConfig

getAttributionScoreSkewThresholdsOrThrow(String key)

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;

Parameter
NameDescription
keyString
Returns
TypeDescription
ThresholdConfig

getDefaultInstanceForType()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstanceForType()
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getMutableAttributionScoreSkewThresholds()

public Map<String,ThresholdConfig> getMutableAttributionScoreSkewThresholds()

Use alternate mutation accessors instead.

Returns
TypeDescription
Map<String,ThresholdConfig>

getMutableSkewThresholds()

public Map<String,ThresholdConfig> getMutableSkewThresholds()

Use alternate mutation accessors instead.

Returns
TypeDescription
Map<String,ThresholdConfig>

getSkewThresholds()

public Map<String,ThresholdConfig> getSkewThresholds()
Returns
TypeDescription
Map<String,ThresholdConfig>

getSkewThresholdsCount()

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;

Returns
TypeDescription
int

getSkewThresholdsMap()

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;

Returns
TypeDescription
Map<String,ThresholdConfig>

getSkewThresholdsOrDefault(String key, ThresholdConfig defaultValue)

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;

Parameters
NameDescription
keyString
defaultValueThresholdConfig
Returns
TypeDescription
ThresholdConfig

getSkewThresholdsOrThrow(String key)

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;

Parameter
NameDescription
keyString
Returns
TypeDescription
ThresholdConfig

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

internalGetMapField(int number)

protected MapField internalGetMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig other)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig other)
Parameter
NameDescription
otherModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

putAllAttributionScoreSkewThresholds(Map<String,ThresholdConfig> values)

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;

Parameter
NameDescription
valuesMap<String,ThresholdConfig>
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

putAllSkewThresholds(Map<String,ThresholdConfig> values)

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;

Parameter
NameDescription
valuesMap<String,ThresholdConfig>
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

putAttributionScoreSkewThresholds(String key, ThresholdConfig value)

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;

Parameters
NameDescription
keyString
valueThresholdConfig
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

putSkewThresholds(String key, ThresholdConfig value)

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;

Parameters
NameDescription
keyString
valueThresholdConfig
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

removeAttributionScoreSkewThresholds(String key)

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;

Parameter
NameDescription
keyString
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

removeSkewThresholds(String key)

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;

Parameter
NameDescription
keyString
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

public final ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder
Overrides