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public static final class ModelExplanation.Builder extends GeneratedMessageV3.Builder<ModelExplanation.Builder> implements ModelExplanationOrBuilderAggregated explanation metrics for a Model over a set of instances.
Protobuf type google.cloud.aiplatform.v1beta1.ModelExplanation
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelExplanation.BuilderImplements
ModelExplanationOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
Methods
addAllMeanAttributions(Iterable<? extends Attribution> values)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
values |
Iterable<? extends com.google.cloud.aiplatform.v1beta1.Attribution> |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
addMeanAttributions(Attribution value)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
Attribution |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
addMeanAttributions(Attribution.Builder builderForValue)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
builderForValue |
Attribution.Builder |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
addMeanAttributions(int index, Attribution value)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameters | |
|---|---|
| Name | Description |
index |
int |
value |
Attribution |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
addMeanAttributions(int index, Attribution.Builder builderForValue)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameters | |
|---|---|
| Name | Description |
index |
int |
builderForValue |
Attribution.Builder |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
Attribution.Builder |
|
addMeanAttributionsBuilder(int index)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
Attribution.Builder |
|
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public ModelExplanation.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
build()
public ModelExplanation build()| Returns | |
|---|---|
| Type | Description |
ModelExplanation |
|
buildPartial()
public ModelExplanation buildPartial()| Returns | |
|---|---|
| Type | Description |
ModelExplanation |
|
clear()
public ModelExplanation.Builder clear()| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
clearField(Descriptors.FieldDescriptor field)
public ModelExplanation.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
clearOneof(Descriptors.OneofDescriptor oneof)
public ModelExplanation.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
clone()
public ModelExplanation.Builder clone()| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
getDefaultInstanceForType()
public ModelExplanation getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
ModelExplanation |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getMeanAttributions(int index)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
Attribution |
|
getMeanAttributionsBuilder(int index)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
Attribution.Builder |
|
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
List<Builder> |
|
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
int |
|
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
List<Attribution> |
|
getMeanAttributionsOrBuilder(int index)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
AttributionOrBuilder |
|
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
List<? extends com.google.cloud.aiplatform.v1beta1.AttributionOrBuilder> |
|
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
mergeFrom(ModelExplanation other)
public ModelExplanation.Builder mergeFrom(ModelExplanation other)| Parameter | |
|---|---|
| Name | Description |
other |
ModelExplanation |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public ModelExplanation.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public ModelExplanation.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
mergeUnknownFields(UnknownFieldSet unknownFields)
public final ModelExplanation.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
removeMeanAttributions(int index)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
setField(Descriptors.FieldDescriptor field, Object value)
public ModelExplanation.Builder setField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
setMeanAttributions(int index, Attribution value)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameters | |
|---|---|
| Name | Description |
index |
int |
value |
Attribution |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
setMeanAttributions(int index, Attribution.Builder builderForValue)
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 can be used to identify which output this attribution is explaining.
The baselineOutputValue, instanceOutputValue and featureAttributions 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 is not populated.
repeated .google.cloud.aiplatform.v1beta1.Attribution mean_attributions = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameters | |
|---|---|
| Name | Description |
index |
int |
builderForValue |
Attribution.Builder |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public ModelExplanation.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
index |
int |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|
setUnknownFields(UnknownFieldSet unknownFields)
public final ModelExplanation.Builder setUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
ModelExplanation.Builder |
|