Class ModelExplanation.Builder
- java.lang.Object
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- com.google.protobuf.AbstractMessageLite.Builder
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- com.google.protobuf.AbstractMessage.Builder<BuilderT>
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- com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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- com.google.cloud.aiplatform.v1beta1.ModelExplanation.Builder
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- All Implemented Interfaces:
ModelExplanationOrBuilder
,com.google.protobuf.Message.Builder
,com.google.protobuf.MessageLite.Builder
,com.google.protobuf.MessageLiteOrBuilder
,com.google.protobuf.MessageOrBuilder
,Cloneable
- Enclosing class:
- ModelExplanation
public static final class ModelExplanation.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder> implements ModelExplanationOrBuilder
Aggregated explanation metrics for a Model over a set of instances.
Protobuf typegoogle.cloud.aiplatform.v1beta1.ModelExplanation
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Method Summary
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Methods inherited from class com.google.protobuf.GeneratedMessageV3.Builder
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3
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Methods inherited from class com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString
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Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageException
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Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
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Method Detail
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
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internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
- Specified by:
internalGetFieldAccessorTable
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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clear
public ModelExplanation.Builder clear()
- Specified by:
clear
in interfacecom.google.protobuf.Message.Builder
- Specified by:
clear
in interfacecom.google.protobuf.MessageLite.Builder
- Overrides:
clear
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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getDescriptorForType
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
- Specified by:
getDescriptorForType
in interfacecom.google.protobuf.Message.Builder
- Specified by:
getDescriptorForType
in interfacecom.google.protobuf.MessageOrBuilder
- Overrides:
getDescriptorForType
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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getDefaultInstanceForType
public ModelExplanation getDefaultInstanceForType()
- Specified by:
getDefaultInstanceForType
in interfacecom.google.protobuf.MessageLiteOrBuilder
- Specified by:
getDefaultInstanceForType
in interfacecom.google.protobuf.MessageOrBuilder
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build
public ModelExplanation build()
- Specified by:
build
in interfacecom.google.protobuf.Message.Builder
- Specified by:
build
in interfacecom.google.protobuf.MessageLite.Builder
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buildPartial
public ModelExplanation buildPartial()
- Specified by:
buildPartial
in interfacecom.google.protobuf.Message.Builder
- Specified by:
buildPartial
in interfacecom.google.protobuf.MessageLite.Builder
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clone
public ModelExplanation.Builder clone()
- Specified by:
clone
in interfacecom.google.protobuf.Message.Builder
- Specified by:
clone
in interfacecom.google.protobuf.MessageLite.Builder
- Overrides:
clone
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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setField
public ModelExplanation.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
- Specified by:
setField
in interfacecom.google.protobuf.Message.Builder
- Overrides:
setField
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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clearField
public ModelExplanation.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
- Specified by:
clearField
in interfacecom.google.protobuf.Message.Builder
- Overrides:
clearField
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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clearOneof
public ModelExplanation.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
- Specified by:
clearOneof
in interfacecom.google.protobuf.Message.Builder
- Overrides:
clearOneof
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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setRepeatedField
public ModelExplanation.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
- Specified by:
setRepeatedField
in interfacecom.google.protobuf.Message.Builder
- Overrides:
setRepeatedField
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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addRepeatedField
public ModelExplanation.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
- Specified by:
addRepeatedField
in interfacecom.google.protobuf.Message.Builder
- Overrides:
addRepeatedField
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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mergeFrom
public ModelExplanation.Builder mergeFrom(com.google.protobuf.Message other)
- Specified by:
mergeFrom
in interfacecom.google.protobuf.Message.Builder
- Overrides:
mergeFrom
in classcom.google.protobuf.AbstractMessage.Builder<ModelExplanation.Builder>
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mergeFrom
public ModelExplanation.Builder mergeFrom(ModelExplanation other)
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isInitialized
public final boolean isInitialized()
- Specified by:
isInitialized
in interfacecom.google.protobuf.MessageLiteOrBuilder
- Overrides:
isInitialized
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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mergeFrom
public ModelExplanation.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
- Specified by:
mergeFrom
in interfacecom.google.protobuf.Message.Builder
- Specified by:
mergeFrom
in interfacecom.google.protobuf.MessageLite.Builder
- Overrides:
mergeFrom
in classcom.google.protobuf.AbstractMessage.Builder<ModelExplanation.Builder>
- Throws:
IOException
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getMeanAttributionsList
public List<Attribution> getMeanAttributionsList()
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
- Specified by:
getMeanAttributionsList
in interfaceModelExplanationOrBuilder
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getMeanAttributionsCount
public int getMeanAttributionsCount()
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
- Specified by:
getMeanAttributionsCount
in interfaceModelExplanationOrBuilder
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getMeanAttributions
public Attribution getMeanAttributions(int index)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
- Specified by:
getMeanAttributions
in interfaceModelExplanationOrBuilder
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setMeanAttributions
public ModelExplanation.Builder setMeanAttributions(int index, Attribution value)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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setMeanAttributions
public ModelExplanation.Builder setMeanAttributions(int index, Attribution.Builder builderForValue)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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addMeanAttributions
public ModelExplanation.Builder addMeanAttributions(Attribution value)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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addMeanAttributions
public ModelExplanation.Builder addMeanAttributions(int index, Attribution value)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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addMeanAttributions
public ModelExplanation.Builder addMeanAttributions(Attribution.Builder builderForValue)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
-
addMeanAttributions
public ModelExplanation.Builder addMeanAttributions(int index, Attribution.Builder builderForValue)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
-
addAllMeanAttributions
public ModelExplanation.Builder addAllMeanAttributions(Iterable<? extends Attribution> values)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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clearMeanAttributions
public ModelExplanation.Builder clearMeanAttributions()
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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removeMeanAttributions
public ModelExplanation.Builder removeMeanAttributions(int index)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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getMeanAttributionsBuilder
public Attribution.Builder getMeanAttributionsBuilder(int index)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
-
getMeanAttributionsOrBuilder
public AttributionOrBuilder getMeanAttributionsOrBuilder(int index)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
- Specified by:
getMeanAttributionsOrBuilder
in interfaceModelExplanationOrBuilder
-
getMeanAttributionsOrBuilderList
public List<? extends AttributionOrBuilder> getMeanAttributionsOrBuilderList()
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
- Specified by:
getMeanAttributionsOrBuilderList
in interfaceModelExplanationOrBuilder
-
addMeanAttributionsBuilder
public Attribution.Builder addMeanAttributionsBuilder()
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
-
addMeanAttributionsBuilder
public Attribution.Builder addMeanAttributionsBuilder(int index)
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
-
getMeanAttributionsBuilderList
public List<Attribution.Builder> getMeanAttributionsBuilderList()
Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. [Attribution.output_index][google.cloud.aiplatform.v1beta1.Attribution.output_index] can be used to identify which output this attribution is explaining. The [baselineOutputValue][google.cloud.aiplatform.v1beta1.Attribution.baseline_output_value], [instanceOutputValue][google.cloud.aiplatform.v1beta1.Attribution.instance_output_value] and [featureAttributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. [Attribution.approximation_error][google.cloud.aiplatform.v1beta1.Attribution.approximation_error] is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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setUnknownFields
public final ModelExplanation.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
- Specified by:
setUnknownFields
in interfacecom.google.protobuf.Message.Builder
- Overrides:
setUnknownFields
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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mergeUnknownFields
public final ModelExplanation.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
- Specified by:
mergeUnknownFields
in interfacecom.google.protobuf.Message.Builder
- Overrides:
mergeUnknownFields
in classcom.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>
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