com.google.cloud.aiplatform.v1beta1

Class ModelExplanation.Builder

java.lang.Object

com.google.protobuf.AbstractMessageLite.Builder

com.google.protobuf.AbstractMessage.Builder<BuilderT>

com.google.protobuf.GeneratedMessageV3.Builder<ModelExplanation.Builder>

com.google.cloud.aiplatform.v1beta1.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 Summary

Modifier and Type	Method and Description
ModelExplanation.Builder	addAllMeanAttributions(Iterable<? extends Attribution> values) Output only.
ModelExplanation.Builder	addMeanAttributions(Attribution.Builder builderForValue) Output only.
ModelExplanation.Builder	addMeanAttributions(Attribution value) Output only.
ModelExplanation.Builder	addMeanAttributions(int index, Attribution.Builder builderForValue) Output only.
ModelExplanation.Builder	addMeanAttributions(int index, Attribution value) Output only.
Attribution.Builder	addMeanAttributionsBuilder() Output only.
Attribution.Builder	addMeanAttributionsBuilder(int index) Output only.
ModelExplanation.Builder	addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
ModelExplanation	build()
ModelExplanation	buildPartial()
ModelExplanation.Builder	clear()
ModelExplanation.Builder	clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
ModelExplanation.Builder	clearMeanAttributions() Output only.
ModelExplanation.Builder	clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
ModelExplanation.Builder	clone()
ModelExplanation	getDefaultInstanceForType()
static com.google.protobuf.Descriptors.Descriptor	getDescriptor()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType()
Attribution	getMeanAttributions(int index) Output only.
Attribution.Builder	getMeanAttributionsBuilder(int index) Output only.
List<Attribution.Builder>	getMeanAttributionsBuilderList() Output only.
int	getMeanAttributionsCount() Output only.
List<Attribution>	getMeanAttributionsList() Output only.
AttributionOrBuilder	getMeanAttributionsOrBuilder(int index) Output only.
List<? extends AttributionOrBuilder>	getMeanAttributionsOrBuilderList() Output only.
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable	internalGetFieldAccessorTable()
boolean	isInitialized()
ModelExplanation.Builder	mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ModelExplanation.Builder	mergeFrom(com.google.protobuf.Message other)
ModelExplanation.Builder	mergeFrom(ModelExplanation other)
ModelExplanation.Builder	mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
ModelExplanation.Builder	removeMeanAttributions(int index) Output only.
ModelExplanation.Builder	setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
ModelExplanation.Builder	setMeanAttributions(int index, Attribution.Builder builderForValue) Output only.
ModelExplanation.Builder	setMeanAttributions(int index, Attribution value) Output only.
ModelExplanation.Builder	setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
ModelExplanation.Builder	setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)

Methods inherited from class com.google.protobuf.GeneratedMessageV3.Builder

getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3

Methods inherited from class com.google.protobuf.AbstractMessage.Builder

findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder

addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.MessageOrBuilder

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

Methods inherited from interface com.google.protobuf.Message.Builder

mergeDelimitedFrom, mergeDelimitedFrom

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>

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.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>