Package com.google.cloud.aiplatform.v1

Class ModelExplanation.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ModelExplanation.Builder>
com.google.cloud.aiplatform.v1.ModelExplanation.Builder
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.GeneratedMessage.Builder<ModelExplanation.Builder> implements ModelExplanationOrBuilder
 Aggregated explanation metrics for a Model over a set of instances.
Protobuf type google.cloud.aiplatform.v1.ModelExplanation

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ModelExplanation.Builder>

    • clear

      public ModelExplanation.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<ModelExplanation.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ModelExplanation.Builder>

    • getDefaultInstanceForType

      public ModelExplanation getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public ModelExplanation build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public ModelExplanation buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • mergeFrom

      public ModelExplanation.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelExplanation.Builder>

    • mergeFrom

      public ModelExplanation.Builder mergeFrom(ModelExplanation other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ModelExplanation.Builder>

    • mergeFrom

      public ModelExplanation.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelExplanation.Builder>
      Throws:
      IOException

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getMeanAttributionsList in interface ModelExplanationOrBuilder

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getMeanAttributionsCount in interface ModelExplanationOrBuilder

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getMeanAttributions in interface ModelExplanationOrBuilder

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getMeanAttributionsOrBuilder in interface ModelExplanationOrBuilder

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getMeanAttributionsOrBuilderList in interface ModelExplanationOrBuilder

    • 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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.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.v1.Attribution.output_index]
 can be used to identify which output this attribution is explaining.

 The
 [baselineOutputValue][google.cloud.aiplatform.v1.Attribution.baseline_output_value],
 [instanceOutputValue][google.cloud.aiplatform.v1.Attribution.instance_output_value]
 and
 [featureAttributions][google.cloud.aiplatform.v1.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.v1.Attribution.approximation_error]
 is not populated.
      repeated .google.cloud.aiplatform.v1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];