com.google.cloud.aiplatform.v1

Interface ModelExplanationOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

ModelExplanation, ModelExplanation.Builder

public interface ModelExplanationOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
Attribution	getMeanAttributions(int index) Output only.
int	getMeanAttributionsCount() Output only.
List<Attribution>	getMeanAttributionsList() Output only.
AttributionOrBuilder	getMeanAttributionsOrBuilder(int index) Output only.
List<? extends AttributionOrBuilder>	getMeanAttributionsOrBuilderList() Output only.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getMeanAttributionsList

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];

getMeanAttributions

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];

getMeanAttributionsCount

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];

getMeanAttributionsOrBuilderList

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];

getMeanAttributionsOrBuilder

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];