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public static final class Attribution.Builder extends GeneratedMessageV3.Builder<Attribution.Builder> implements AttributionOrBuilder
Attribution that explains a particular prediction output.
Protobuf type google.cloud.aiplatform.v1.Attribution
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > Attribution.BuilderImplements
AttributionOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
Methods
addAllOutputIndex(Iterable<? extends Integer> values)
public Attribution.Builder addAllOutputIndex(Iterable<? extends Integer> values)
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];
Name | Description |
values | Iterable<? extends java.lang.Integer> The outputIndex to add. |
Type | Description |
Attribution.Builder | This builder for chaining. |
addOutputIndex(int value)
public Attribution.Builder addOutputIndex(int value)
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];
Name | Description |
value | int The outputIndex to add. |
Type | Description |
Attribution.Builder | This builder for chaining. |
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public Attribution.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
Attribution.Builder |
build()
public Attribution build()
Type | Description |
Attribution |
buildPartial()
public Attribution buildPartial()
Type | Description |
Attribution |
clear()
public Attribution.Builder clear()
Type | Description |
Attribution.Builder |
clearApproximationError()
public Attribution.Builder clearApproximationError()
Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions.
- For Sampled Shapley attribution, increasing path_count might reduce the error.
- For Integrated Gradients attribution, increasing step_count might reduce the error.
- For XRAI attribution, increasing step_count might reduce the error. See this introduction for more information.
double approximation_error = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
Attribution.Builder | This builder for chaining. |
clearBaselineOutputValue()
public Attribution.Builder clearBaselineOutputValue()
Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank > 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged.
double baseline_output_value = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
Attribution.Builder | This builder for chaining. |
clearFeatureAttributions()
public Attribution.Builder clearFeatureAttributions()
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Type | Description |
Attribution.Builder |
clearField(Descriptors.FieldDescriptor field)
public Attribution.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
Attribution.Builder |
clearInstanceOutputValue()
public Attribution.Builder clearInstanceOutputValue()
Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.
double instance_output_value = 2 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
Attribution.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public Attribution.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
Attribution.Builder |
clearOutputDisplayName()
public Attribution.Builder clearOutputDisplayName()
Output only. The display name of the output identified by 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];
Type | Description |
Attribution.Builder | This builder for chaining. |
clearOutputIndex()
public Attribution.Builder clearOutputIndex()
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];
Type | Description |
Attribution.Builder | This builder for chaining. |
clearOutputName()
public Attribution.Builder clearOutputName()
Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
Attribution.Builder | This builder for chaining. |
clone()
public Attribution.Builder clone()
Type | Description |
Attribution.Builder |
getApproximationError()
public double getApproximationError()
Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions.
- For Sampled Shapley attribution, increasing path_count might reduce the error.
- For Integrated Gradients attribution, increasing step_count might reduce the error.
- For XRAI attribution, increasing step_count might reduce the error. See this introduction for more information.
double approximation_error = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
double | The approximationError. |
getBaselineOutputValue()
public double getBaselineOutputValue()
Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank > 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged.
double baseline_output_value = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
double | The baselineOutputValue. |
getDefaultInstanceForType()
public Attribution getDefaultInstanceForType()
Type | Description |
Attribution |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
getFeatureAttributions()
public Value getFeatureAttributions()
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Type | Description |
Value | The featureAttributions. |
getFeatureAttributionsBuilder()
public Value.Builder getFeatureAttributionsBuilder()
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Type | Description |
Builder |
getFeatureAttributionsOrBuilder()
public ValueOrBuilder getFeatureAttributionsOrBuilder()
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Type | Description |
ValueOrBuilder |
getInstanceOutputValue()
public double getInstanceOutputValue()
Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.
double instance_output_value = 2 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
double | The instanceOutputValue. |
getOutputDisplayName()
public String getOutputDisplayName()
Output only. The display name of the output identified by 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];
Type | Description |
String | The outputDisplayName. |
getOutputDisplayNameBytes()
public ByteString getOutputDisplayNameBytes()
Output only. The display name of the output identified by 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];
Type | Description |
ByteString | The bytes for outputDisplayName. |
getOutputIndex(int index)
public 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];
Name | Description |
index | int The index of the element to return. |
Type | Description |
int | The outputIndex at the given index. |
getOutputIndexCount()
public 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];
Type | Description |
int | The count of outputIndex. |
getOutputIndexList()
public 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];
Type | Description |
List<Integer> | A list containing the outputIndex. |
getOutputName()
public String getOutputName()
Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
String | The outputName. |
getOutputNameBytes()
public ByteString getOutputNameBytes()
Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
ByteString | The bytes for outputName. |
hasFeatureAttributions()
public boolean hasFeatureAttributions()
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Type | Description |
boolean | Whether the featureAttributions field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
mergeFeatureAttributions(Value value)
public Attribution.Builder mergeFeatureAttributions(Value value)
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Name | Description |
value | Value |
Type | Description |
Attribution.Builder |
mergeFrom(Attribution other)
public Attribution.Builder mergeFrom(Attribution other)
Name | Description |
other | Attribution |
Type | Description |
Attribution.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public Attribution.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
Attribution.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public Attribution.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
Attribution.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final Attribution.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
Attribution.Builder |
setApproximationError(double value)
public Attribution.Builder setApproximationError(double value)
Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions.
- For Sampled Shapley attribution, increasing path_count might reduce the error.
- For Integrated Gradients attribution, increasing step_count might reduce the error.
- For XRAI attribution, increasing step_count might reduce the error. See this introduction for more information.
double approximation_error = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | double The approximationError to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setBaselineOutputValue(double value)
public Attribution.Builder setBaselineOutputValue(double value)
Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank > 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged.
double baseline_output_value = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | double The baselineOutputValue to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setFeatureAttributions(Value value)
public Attribution.Builder setFeatureAttributions(Value value)
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Name | Description |
value | Value |
Type | Description |
Attribution.Builder |
setFeatureAttributions(Value.Builder builderForValue)
public Attribution.Builder setFeatureAttributions(Value.Builder builderForValue)
Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance 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.
- If the feature is an array of scalar values, the attribution value is an array.
- If the feature is a struct, the attribution value is a struct. 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 field, pointed to by the ExplanationSpec field of the 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];
Name | Description |
builderForValue | Builder |
Type | Description |
Attribution.Builder |
setField(Descriptors.FieldDescriptor field, Object value)
public Attribution.Builder setField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
Attribution.Builder |
setInstanceOutputValue(double value)
public Attribution.Builder setInstanceOutputValue(double value)
Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.
double instance_output_value = 2 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | double The instanceOutputValue to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setOutputDisplayName(String value)
public Attribution.Builder setOutputDisplayName(String value)
Output only. The display name of the output identified by 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];
Name | Description |
value | String The outputDisplayName to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setOutputDisplayNameBytes(ByteString value)
public Attribution.Builder setOutputDisplayNameBytes(ByteString value)
Output only. The display name of the output identified by 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];
Name | Description |
value | ByteString The bytes for outputDisplayName to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setOutputIndex(int index, int value)
public Attribution.Builder setOutputIndex(int index, int value)
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];
Name | Description |
index | int The index to set the value at. |
value | int The outputIndex to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setOutputName(String value)
public Attribution.Builder setOutputName(String value)
Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | String The outputName to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setOutputNameBytes(ByteString value)
public Attribution.Builder setOutputNameBytes(ByteString value)
Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | ByteString The bytes for outputName to set. |
Type | Description |
Attribution.Builder | This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public Attribution.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
Attribution.Builder |
setUnknownFields(UnknownFieldSet unknownFields)
public final Attribution.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
Attribution.Builder |