Interface AttributionOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
Attribution, Attribution.Builder

@Generated public interface AttributionOrBuilder extends com.google.protobuf.MessageOrBuilder
  • Method Details

    • getBaselineOutputValue

      double getBaselineOutputValue()
       Output only. Model predicted output if the input instance is constructed
       from the baselines of all the features defined in
       [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
       The field name of the output is determined by the key in
       [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs].
      
       If the Model's predicted output has multiple dimensions (rank > 1), this is
       the value in the output located by
       [output_index][google.cloud.aiplatform.v1.Attribution.output_index].
      
       If there are multiple baselines, their output values are averaged.
       
      double baseline_output_value = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The baselineOutputValue.
    • getInstanceOutputValue

      double getInstanceOutputValue()
       Output only. Model predicted output on the corresponding [explanation
       instance][ExplainRequest.instances]. The field name of the output is
       determined by the key in
       [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs].
      
       If the Model predicted output has multiple dimensions, this is the value in
       the output located by
       [output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      double instance_output_value = 2 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The instanceOutputValue.
    • hasFeatureAttributions

      boolean hasFeatureAttributions()
       Output only. Attributions of each explained feature. Features are extracted
       from the [prediction
       instances][google.cloud.aiplatform.v1.ExplainRequest.instances] according
       to [explanation metadata for
       inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
      
       The value is a struct, whose keys are the name of the feature. The values
       are how much the feature in the
       [instance][google.cloud.aiplatform.v1.ExplainRequest.instances] contributed
       to the predicted result.
      
       The format of the value is determined by the feature's input format:
      
       * If the feature is a scalar value, the attribution value is a
       [floating number][google.protobuf.Value.number_value].
      
       * If the feature is an array of scalar values, the attribution value is
       an [array][google.protobuf.Value.list_value].
      
       * If the feature is a struct, the attribution value is a
       [struct][google.protobuf.Value.struct_value]. The keys in the
       attribution value struct are the same as the keys in the feature
       struct. The formats of the values in the attribution struct are
       determined by the formats of the values in the feature struct.
      
       The
       [ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri]
       field, pointed to by the
       [ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] field of the
       [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
       object, points to the schema file that describes the features and their
       attribution values (if it is populated).
       
      .google.protobuf.Value feature_attributions = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      Whether the featureAttributions field is set.
    • getFeatureAttributions

      com.google.protobuf.Value getFeatureAttributions()
       Output only. Attributions of each explained feature. Features are extracted
       from the [prediction
       instances][google.cloud.aiplatform.v1.ExplainRequest.instances] according
       to [explanation metadata for
       inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
      
       The value is a struct, whose keys are the name of the feature. The values
       are how much the feature in the
       [instance][google.cloud.aiplatform.v1.ExplainRequest.instances] contributed
       to the predicted result.
      
       The format of the value is determined by the feature's input format:
      
       * If the feature is a scalar value, the attribution value is a
       [floating number][google.protobuf.Value.number_value].
      
       * If the feature is an array of scalar values, the attribution value is
       an [array][google.protobuf.Value.list_value].
      
       * If the feature is a struct, the attribution value is a
       [struct][google.protobuf.Value.struct_value]. The keys in the
       attribution value struct are the same as the keys in the feature
       struct. The formats of the values in the attribution struct are
       determined by the formats of the values in the feature struct.
      
       The
       [ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri]
       field, pointed to by the
       [ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] field of the
       [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
       object, points to the schema file that describes the features and their
       attribution values (if it is populated).
       
      .google.protobuf.Value feature_attributions = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The featureAttributions.
    • getFeatureAttributionsOrBuilder

      com.google.protobuf.ValueOrBuilder getFeatureAttributionsOrBuilder()
       Output only. Attributions of each explained feature. Features are extracted
       from the [prediction
       instances][google.cloud.aiplatform.v1.ExplainRequest.instances] according
       to [explanation metadata for
       inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
      
       The value is a struct, whose keys are the name of the feature. The values
       are how much the feature in the
       [instance][google.cloud.aiplatform.v1.ExplainRequest.instances] contributed
       to the predicted result.
      
       The format of the value is determined by the feature's input format:
      
       * If the feature is a scalar value, the attribution value is a
       [floating number][google.protobuf.Value.number_value].
      
       * If the feature is an array of scalar values, the attribution value is
       an [array][google.protobuf.Value.list_value].
      
       * If the feature is a struct, the attribution value is a
       [struct][google.protobuf.Value.struct_value]. The keys in the
       attribution value struct are the same as the keys in the feature
       struct. The formats of the values in the attribution struct are
       determined by the formats of the values in the feature struct.
      
       The
       [ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri]
       field, pointed to by the
       [ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] field of the
       [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
       object, points to the schema file that describes the features and their
       attribution values (if it is populated).
       
      .google.protobuf.Value feature_attributions = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getOutputIndexList

      List<Integer> getOutputIndexList()
       Output only. The index that locates the explained prediction output.
      
       If the prediction output is a scalar value, output_index is not populated.
       If the prediction output has multiple dimensions, the length of the
       output_index list is the same as the number of dimensions of the output.
       The i-th element in output_index is the element index of the i-th dimension
       of the output vector. Indices start from 0.
       
      repeated int32 output_index = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      A list containing the outputIndex.
    • getOutputIndexCount

      int getOutputIndexCount()
       Output only. The index that locates the explained prediction output.
      
       If the prediction output is a scalar value, output_index is not populated.
       If the prediction output has multiple dimensions, the length of the
       output_index list is the same as the number of dimensions of the output.
       The i-th element in output_index is the element index of the i-th dimension
       of the output vector. Indices start from 0.
       
      repeated int32 output_index = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The count of outputIndex.
    • getOutputIndex

      int getOutputIndex(int index)
       Output only. The index that locates the explained prediction output.
      
       If the prediction output is a scalar value, output_index is not populated.
       If the prediction output has multiple dimensions, the length of the
       output_index list is the same as the number of dimensions of the output.
       The i-th element in output_index is the element index of the i-th dimension
       of the output vector. Indices start from 0.
       
      repeated int32 output_index = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      index - The index of the element to return.
      Returns:
      The outputIndex at the given index.
    • getOutputDisplayName

      String getOutputDisplayName()
       Output only. The display name of the output identified by
       [output_index][google.cloud.aiplatform.v1.Attribution.output_index]. For
       example, the predicted class name by a multi-classification Model.
      
       This field is only populated iff the Model predicts display names as a
       separate field along with the explained output. The predicted display name
       must has the same shape of the explained output, and can be located using
       output_index.
       
      string output_display_name = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The outputDisplayName.
    • getOutputDisplayNameBytes

      com.google.protobuf.ByteString getOutputDisplayNameBytes()
       Output only. The display name of the output identified by
       [output_index][google.cloud.aiplatform.v1.Attribution.output_index]. For
       example, the predicted class name by a multi-classification Model.
      
       This field is only populated iff the Model predicts display names as a
       separate field along with the explained output. The predicted display name
       must has the same shape of the explained output, and can be located using
       output_index.
       
      string output_display_name = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The bytes for outputDisplayName.
    • getApproximationError

      double getApproximationError()
       Output only. Error of
       [feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
       caused by approximation used in the explanation method. Lower value means
       more precise attributions.
      
       * For Sampled Shapley
       [attribution][google.cloud.aiplatform.v1.ExplanationParameters.sampled_shapley_attribution],
       increasing
       [path_count][google.cloud.aiplatform.v1.SampledShapleyAttribution.path_count]
       might reduce the error.
       * For Integrated Gradients
       [attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
       increasing
       [step_count][google.cloud.aiplatform.v1.IntegratedGradientsAttribution.step_count]
       might reduce the error.
       * For [XRAI
       attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
       increasing
       [step_count][google.cloud.aiplatform.v1.XraiAttribution.step_count] might
       reduce the error.
      
       See [this introduction](/vertex-ai/docs/explainable-ai/overview)
       for more information.
       
      double approximation_error = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The approximationError.
    • getOutputName

      String getOutputName()
       Output only. Name of the explain output. Specified as the key in
       [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs].
       
      string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The outputName.
    • getOutputNameBytes

      com.google.protobuf.ByteString getOutputNameBytes()
       Output only. Name of the explain output. Specified as the key in
       [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs].
       
      string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The bytes for outputName.