public static final class ModelMonitoringObjectiveConfig.ExplanationConfig.Builder extends GeneratedMessageV3.Builder<ModelMonitoringObjectiveConfig.ExplanationConfig.Builder> implements ModelMonitoringObjectiveConfig.ExplanationConfigOrBuilder
The config for integrated with Explainable AI. Only applicable if the Model
has explanation_spec populated.
Protobuf type
google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
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public ModelMonitoringObjectiveConfig.ExplanationConfig build()
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public ModelMonitoringObjectiveConfig.ExplanationConfig buildPartial()
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder clear()
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder clearEnableFeatureAttributes()
If want to analyze the Explainable AI feature attribute scores or not.
If set to true, Vertex AI will log the feature attributions from
explain response and do the skew/drift detection for them.
bool enable_feature_attributes = 1;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder clearExplanationBaseline()
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder clearField(Descriptors.FieldDescriptor field)
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder clone()
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public ModelMonitoringObjectiveConfig.ExplanationConfig getDefaultInstanceForType()
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public static final Descriptors.Descriptor getDescriptor()
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public Descriptors.Descriptor getDescriptorForType()
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public boolean getEnableFeatureAttributes()
If want to analyze the Explainable AI feature attribute scores or not.
If set to true, Vertex AI will log the feature attributions from
explain response and do the skew/drift detection for them.
bool enable_feature_attributes = 1;
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Type | Description |
boolean | The enableFeatureAttributes.
|
public ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline getExplanationBaseline()
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline.Builder getExplanationBaselineBuilder()
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaselineOrBuilder getExplanationBaselineOrBuilder()
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public boolean hasExplanationBaseline()
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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Type | Description |
boolean | Whether the explanationBaseline field is set.
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protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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public final boolean isInitialized()
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder mergeExplanationBaseline(ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline value)
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder mergeFrom(ModelMonitoringObjectiveConfig.ExplanationConfig other)
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder mergeFrom(Message other)
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public final ModelMonitoringObjectiveConfig.ExplanationConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder setEnableFeatureAttributes(boolean value)
If want to analyze the Explainable AI feature attribute scores or not.
If set to true, Vertex AI will log the feature attributions from
explain response and do the skew/drift detection for them.
bool enable_feature_attributes = 1;
Parameter
Name | Description |
value | boolean
The enableFeatureAttributes to set.
|
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder setExplanationBaseline(ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline value)
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder setExplanationBaseline(ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline.Builder builderForValue)
Predictions generated by the BatchPredictionJob using baseline dataset.
.google.cloud.aiplatform.v1beta1.ModelMonitoringObjectiveConfig.ExplanationConfig.ExplanationBaseline explanation_baseline = 2;
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
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public ModelMonitoringObjectiveConfig.ExplanationConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
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public final ModelMonitoringObjectiveConfig.ExplanationConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
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