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
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
public static final int ATTRIBUTION_SCORE_SKEW_THRESHOLDS_FIELD_NUMBER
Field Value |
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Type | Description |
int | |
public static final int DEFAULT_SKEW_THRESHOLD_FIELD_NUMBER
Field Value |
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Type | Description |
int | |
public static final int SKEW_THRESHOLDS_FIELD_NUMBER
Field Value |
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Type | Description |
int | |
Static Methods
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilder()
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilder(ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig prototype)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseDelimitedFrom(InputStream input)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(byte[] data)
Parameter |
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Name | Description |
data | byte[]
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public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteString data)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(CodedInputStream input)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(InputStream input)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteBuffer data)
public static ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig> parser()
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;
Parameter |
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Name | Description |
key | String
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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 |
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Name | Description |
key | String
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public boolean equals(Object obj)
Parameter |
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Name | Description |
obj | Object
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Overrides
public Map<String,ThresholdConfig> getAttributionScoreSkewThresholds()
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 |
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Type | Description |
int | |
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;
Parameter |
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Name | Description |
key | String
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public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig getDefaultInstanceForType()
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.v1.ThresholdConfig default_skew_threshold = 6;
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.v1.ThresholdConfig default_skew_threshold = 6;
public Parser<ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig> getParserForType()
Overrides
public int getSerializedSize()
Returns |
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Type | Description |
int | |
Overrides
public Map<String,ThresholdConfig> getSkewThresholds()
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 |
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Type | Description |
int | |
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;
Parameter |
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Name | Description |
key | String
|
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.v1.ThresholdConfig default_skew_threshold = 6;
Returns |
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Type | Description |
boolean | Whether the defaultSkewThreshold field is set.
|
Returns |
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Type | Description |
int | |
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
Parameter |
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Name | Description |
number | int
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Returns |
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Type | Description |
com.google.protobuf.MapFieldReflectionAccessor | |
Overrides
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
public final boolean isInitialized()
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilderForType()
protected ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Overrides
public ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides