Package com.google.cloud.aiplatform.v1beta1

Class 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.GeneratedMessageV3.Builder<ModelExplanation.Builder>
implements ModelExplanationOrBuilder
     Aggregated explanation metrics for a Model over a set of instances.
    Protobuf type google.cloud.aiplatform.v1beta1.ModelExplanation

    • Method Detail

      • getDescriptor

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

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.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.GeneratedMessageV3.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.GeneratedMessageV3.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

      • clone

        public ModelExplanation.Builder clone()
        Specified by:
        clone in interface com.google.protobuf.Message.Builder
        Specified by:
        clone in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clone in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

      • setField

        public ModelExplanation.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                         Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

      • clearField

        public ModelExplanation.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

      • clearOneof

        public ModelExplanation.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

      • setRepeatedField

        public ModelExplanation.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                 int index,
                                                 Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

      • addRepeatedField

        public ModelExplanation.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                 Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.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>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.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.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 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.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 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.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 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.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];

      • 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];

      • 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];

      • 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];

      • 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];

      • 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];

      • 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];

      • 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 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.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 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.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];

      • setUnknownFields

        public final ModelExplanation.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

      • mergeUnknownFields

        public final ModelExplanation.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>