Class ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig (3.21.0)

Version 3.21.0

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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.v1beta1.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Inheritance

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

Implements

ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfigOrBuilder

Inherited Members

AbstractMessage.equals(Object)

AbstractMessage.findInitializationErrors()

AbstractMessage.getInitializationErrorString()

AbstractMessage.hashBoolean(boolean)

AbstractMessage.hashCode()

AbstractMessage.hashEnum(Internal.EnumLite)

AbstractMessage.hashEnumList(List<? extends Internal.EnumLite>)

AbstractMessage.hashFields(int,Map<Descriptors.FieldDescriptor,Object>)

AbstractMessage.hashLong(long)

AbstractMessage.toString()

AbstractMessageLite.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.checkByteStringIsUtf8(ByteString)

AbstractMessageLite.toByteArray()

AbstractMessageLite.toByteString()

AbstractMessageLite.writeDelimitedTo(OutputStream)

AbstractMessageLite.writeTo(OutputStream)

com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)

GeneratedMessageV3.<M>parseDelimitedWithIOException(Parser<M>,InputStream)

GeneratedMessageV3.<M>parseDelimitedWithIOException(Parser<M>,InputStream,ExtensionRegistryLite)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,CodedInputStream)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,CodedInputStream,ExtensionRegistryLite)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,InputStream)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,InputStream,ExtensionRegistryLite)

GeneratedMessageV3.<V>serializeBooleanMapTo(CodedOutputStream,MapField<Boolean,V>,MapEntry<Boolean,V>,int)

GeneratedMessageV3.<V>serializeIntegerMapTo(CodedOutputStream,MapField<Integer,V>,MapEntry<Integer,V>,int)

GeneratedMessageV3.<V>serializeLongMapTo(CodedOutputStream,MapField<Long,V>,MapEntry<Long,V>,int)

GeneratedMessageV3.<V>serializeStringMapTo(CodedOutputStream,MapField<String,V>,MapEntry<String,V>,int)

GeneratedMessageV3.canUseUnsafe()

GeneratedMessageV3.computeStringSize(int,Object)

GeneratedMessageV3.computeStringSizeNoTag(Object)

GeneratedMessageV3.emptyBooleanList()

GeneratedMessageV3.emptyDoubleList()

GeneratedMessageV3.emptyFloatList()

GeneratedMessageV3.emptyIntList()

GeneratedMessageV3.emptyLongList()

GeneratedMessageV3.getAllFields()

GeneratedMessageV3.getDescriptorForType()

GeneratedMessageV3.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.getParserForType()

GeneratedMessageV3.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.getSerializedSize()

GeneratedMessageV3.getUnknownFields()

GeneratedMessageV3.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.internalGetFieldAccessorTable()

GeneratedMessageV3.internalGetMapField(int)

GeneratedMessageV3.isInitialized()

GeneratedMessageV3.isStringEmpty(Object)

GeneratedMessageV3.makeExtensionsImmutable()

GeneratedMessageV3.mergeFromAndMakeImmutableInternal(CodedInputStream,ExtensionRegistryLite)

GeneratedMessageV3.mutableCopy(Internal.BooleanList)

GeneratedMessageV3.mutableCopy(Internal.DoubleList)

GeneratedMessageV3.mutableCopy(Internal.FloatList)

GeneratedMessageV3.mutableCopy(Internal.IntList)

GeneratedMessageV3.mutableCopy(Internal.LongList)

GeneratedMessageV3.newBooleanList()

GeneratedMessageV3.newBuilderForType(AbstractMessage.BuilderParent)

GeneratedMessageV3.newBuilderForType(GeneratedMessageV3.BuilderParent)

GeneratedMessageV3.newDoubleList()

GeneratedMessageV3.newFloatList()

GeneratedMessageV3.newInstance(GeneratedMessageV3.UnusedPrivateParameter)

GeneratedMessageV3.newIntList()

GeneratedMessageV3.newLongList()

GeneratedMessageV3.parseUnknownField(CodedInputStream,UnknownFieldSet.Builder,ExtensionRegistryLite,int)

GeneratedMessageV3.parseUnknownFieldProto3(CodedInputStream,UnknownFieldSet.Builder,ExtensionRegistryLite,int)

GeneratedMessageV3.writeReplace()

GeneratedMessageV3.writeString(CodedOutputStream,int,Object)

GeneratedMessageV3.writeStringNoTag(CodedOutputStream,Object)

GeneratedMessageV3.writeTo(CodedOutputStream)

Object.clone()

Object.finalize()

Object.getClass()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Fields

ATTRIBUTION_SCORE_SKEW_THRESHOLDS_FIELD_NUMBER

public static final int ATTRIBUTION_SCORE_SKEW_THRESHOLDS_FIELD_NUMBER

Field Value
Type	Description
int

DEFAULT_SKEW_THRESHOLD_FIELD_NUMBER

public static final int DEFAULT_SKEW_THRESHOLD_FIELD_NUMBER

Field Value
Type	Description
int

SKEW_THRESHOLDS_FIELD_NUMBER

public static final int SKEW_THRESHOLDS_FIELD_NUMBER

Field Value
Type	Description
int

Static Methods

getDefaultInstance()

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstance()

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

newBuilder()

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilder()

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

newBuilder(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig prototype)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilder(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig prototype)

Parameter
Name	Description
prototype	ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

parseDelimitedFrom(InputStream input)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseDelimitedFrom(InputStream input)

Parameter
Name	Description
input	InputStream

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	InputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
IOException

parseFrom(byte[] data)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(byte[] data)

Parameter
Name	Description
data	byte[]

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
data	byte[]
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteString data)

Parameter
Name	Description
data	ByteString

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
data	ByteString
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(CodedInputStream input)

Parameter
Name	Description
input	CodedInputStream

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
IOException

parseFrom(InputStream input)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(InputStream input)

Parameter
Name	Description
input	InputStream

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	InputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
IOException

parseFrom(ByteBuffer data)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteBuffer data)

Parameter
Name	Description
data	ByteBuffer

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
data	ByteBuffer
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

Exceptions
Type	Description
InvalidProtocolBufferException

parser()

public static Parser<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig> parser()

Returns
Type	Description
Parser<TrainingPredictionSkewDetectionConfig>

Methods

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.v1beta1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Parameter
Name	Description
key	String

Returns
Type	Description
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.v1beta1.ThresholdConfig> skew_thresholds = 1;

Parameter
Name	Description
key	String

Returns
Type	Description
boolean

equals(Object obj)

public boolean equals(Object obj)

Parameter
Name	Description
obj	Object

Returns
Type	Description
boolean

Overrides

AbstractMessage.equals(Object other)

getAttributionScoreSkewThresholds()

public Map<String,ThresholdConfig> getAttributionScoreSkewThresholds()

Use #getAttributionScoreSkewThresholdsMap() instead.

Returns
Type	Description
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.v1beta1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Returns
Type	Description
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.v1beta1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Returns
Type	Description
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.v1beta1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Parameters
Name	Description
key	String
defaultValue	ThresholdConfig

Returns
Type	Description
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.v1beta1.ThresholdConfig> attribution_score_skew_thresholds = 2;

Parameter
Name	Description
key	String

Returns
Type	Description
ThresholdConfig

getDefaultInstanceForType()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstanceForType()

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig

getDefaultSkewThreshold()

public ThresholdConfig 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.

.google.cloud.aiplatform.v1beta1.ThresholdConfig default_skew_threshold = 6;

Returns
Type	Description
ThresholdConfig	The defaultSkewThreshold.

getDefaultSkewThresholdOrBuilder()

public ThresholdConfigOrBuilder getDefaultSkewThresholdOrBuilder()

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.

.google.cloud.aiplatform.v1beta1.ThresholdConfig default_skew_threshold = 6;

Returns
Type	Description
ThresholdConfigOrBuilder

getParserForType()

public Parser<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig> getParserForType()

Returns
Type	Description
Parser<TrainingPredictionSkewDetectionConfig>

Overrides

GeneratedMessageV3.getParserForType()

getSerializedSize()

public int getSerializedSize()

Returns
Type	Description
int

Overrides

GeneratedMessageV3.getSerializedSize()

getSkewThresholds()

public Map<String,ThresholdConfig> getSkewThresholds()

Use #getSkewThresholdsMap() instead.

Returns
Type	Description
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.v1beta1.ThresholdConfig> skew_thresholds = 1;

Returns
Type	Description
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.v1beta1.ThresholdConfig> skew_thresholds = 1;

Returns
Type	Description
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.v1beta1.ThresholdConfig> skew_thresholds = 1;

Parameters
Name	Description
key	String
defaultValue	ThresholdConfig

Returns
Type	Description
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.v1beta1.ThresholdConfig> skew_thresholds = 1;

Parameter
Name	Description
key	String

Returns
Type	Description
ThresholdConfig

hasDefaultSkewThreshold()

public boolean hasDefaultSkewThreshold()

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.

.google.cloud.aiplatform.v1beta1.ThresholdConfig default_skew_threshold = 6;

Returns
Type	Description
boolean	Whether the defaultSkewThreshold field is set.

hashCode()

public int hashCode()

Returns
Type	Description
int

Overrides

AbstractMessage.hashCode()

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.internalGetFieldAccessorTable()

internalGetMapField(int number)

protected MapField internalGetMapField(int number)

Parameter
Name	Description
number	int

Returns
Type	Description
MapField

Overrides

GeneratedMessageV3.internalGetMapField(int fieldNumber)

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.isInitialized()

newBuilderForType()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilderForType()

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)

Parameter
Name	Description
parent	BuilderParent

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

Overrides

GeneratedMessageV3.newBuilderForType(GeneratedMessageV3.BuilderParent parent)

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

Parameter
Name	Description
unused	UnusedPrivateParameter

Returns
Type	Description
Object

Overrides

GeneratedMessageV3.newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

toBuilder()

public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder toBuilder()

Returns
Type	Description
ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)

Parameter
Name	Description
output	CodedOutputStream

Overrides

GeneratedMessageV3.writeTo(CodedOutputStream output)

Exceptions
Type	Description
IOException