public interface AttributionOrBuilder
extends com.google.protobuf.MessageOrBuilder
| Modifier and Type | Method and Description |
|---|---|
double |
getApproximationError()
Output only.
|
double |
getBaselineOutputValue()
Output only.
|
com.google.protobuf.Value |
getFeatureAttributions()
Output only.
|
com.google.protobuf.ValueOrBuilder |
getFeatureAttributionsOrBuilder()
Output only.
|
double |
getInstanceOutputValue()
Output only.
|
String |
getOutputDisplayName()
Output only.
|
com.google.protobuf.ByteString |
getOutputDisplayNameBytes()
Output only.
|
int |
getOutputIndex(int index)
Output only.
|
int |
getOutputIndexCount()
Output only.
|
List<Integer> |
getOutputIndexList()
Output only.
|
String |
getOutputName()
Output only.
|
com.google.protobuf.ByteString |
getOutputNameBytes()
Output only.
|
boolean |
hasFeatureAttributions()
Output only.
|
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneofdouble getBaselineOutputValue()
Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs]. The field name of the output is determined by the key in [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs]. If the Model's predicted output has multiple dimensions (rank > 1), this is the value in the output located by [output_index][google.cloud.aiplatform.v1.Attribution.output_index]. If there are multiple baselines, their output values are averaged.
double baseline_output_value = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];double getInstanceOutputValue()
Output only. Model predicted output on the corresponding [explanation instance][ExplainRequest.instances]. The field name of the output is determined by the key in [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs]. If the Model predicted output has multiple dimensions, this is the value in the output located by [output_index][google.cloud.aiplatform.v1.Attribution.output_index].
double instance_output_value = 2 [(.google.api.field_behavior) = OUTPUT_ONLY];boolean hasFeatureAttributions()
Output only. Attributions of each explained feature. Features are extracted
from the [prediction
instances][google.cloud.aiplatform.v1.ExplainRequest.instances] according
to [explanation metadata for
inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
The value is a struct, whose keys are the name of the feature. The values
are how much the feature in the
[instance][google.cloud.aiplatform.v1.ExplainRequest.instances] contributed
to the predicted result.
The format of the value is determined by the feature's input format:
* If the feature is a scalar value, the attribution value is a
[floating number][google.protobuf.Value.number_value].
* If the feature is an array of scalar values, the attribution value is
an [array][google.protobuf.Value.list_value].
* If the feature is a struct, the attribution value is a
[struct][google.protobuf.Value.struct_value]. The keys in the
attribution value struct are the same as the keys in the feature
struct. The formats of the values in the attribution struct are
determined by the formats of the values in the feature struct.
The
[ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri]
field, pointed to by the
[ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] field of the
[Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
object, points to the schema file that describes the features and their
attribution values (if it is populated).
.google.protobuf.Value feature_attributions = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
com.google.protobuf.Value getFeatureAttributions()
Output only. Attributions of each explained feature. Features are extracted
from the [prediction
instances][google.cloud.aiplatform.v1.ExplainRequest.instances] according
to [explanation metadata for
inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
The value is a struct, whose keys are the name of the feature. The values
are how much the feature in the
[instance][google.cloud.aiplatform.v1.ExplainRequest.instances] contributed
to the predicted result.
The format of the value is determined by the feature's input format:
* If the feature is a scalar value, the attribution value is a
[floating number][google.protobuf.Value.number_value].
* If the feature is an array of scalar values, the attribution value is
an [array][google.protobuf.Value.list_value].
* If the feature is a struct, the attribution value is a
[struct][google.protobuf.Value.struct_value]. The keys in the
attribution value struct are the same as the keys in the feature
struct. The formats of the values in the attribution struct are
determined by the formats of the values in the feature struct.
The
[ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri]
field, pointed to by the
[ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] field of the
[Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
object, points to the schema file that describes the features and their
attribution values (if it is populated).
.google.protobuf.Value feature_attributions = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
com.google.protobuf.ValueOrBuilder getFeatureAttributionsOrBuilder()
Output only. Attributions of each explained feature. Features are extracted
from the [prediction
instances][google.cloud.aiplatform.v1.ExplainRequest.instances] according
to [explanation metadata for
inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
The value is a struct, whose keys are the name of the feature. The values
are how much the feature in the
[instance][google.cloud.aiplatform.v1.ExplainRequest.instances] contributed
to the predicted result.
The format of the value is determined by the feature's input format:
* If the feature is a scalar value, the attribution value is a
[floating number][google.protobuf.Value.number_value].
* If the feature is an array of scalar values, the attribution value is
an [array][google.protobuf.Value.list_value].
* If the feature is a struct, the attribution value is a
[struct][google.protobuf.Value.struct_value]. The keys in the
attribution value struct are the same as the keys in the feature
struct. The formats of the values in the attribution struct are
determined by the formats of the values in the feature struct.
The
[ExplanationMetadata.feature_attributions_schema_uri][google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri]
field, pointed to by the
[ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] field of the
[Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
object, points to the schema file that describes the features and their
attribution values (if it is populated).
.google.protobuf.Value feature_attributions = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
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];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];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];index - The index of the element to return.String getOutputDisplayName()
Output only. The display name of the output identified by [output_index][google.cloud.aiplatform.v1.Attribution.output_index]. For example, the predicted class name by a multi-classification Model. This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index.
string output_display_name = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];com.google.protobuf.ByteString getOutputDisplayNameBytes()
Output only. The display name of the output identified by [output_index][google.cloud.aiplatform.v1.Attribution.output_index]. For example, the predicted class name by a multi-classification Model. This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index.
string output_display_name = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];double getApproximationError()
Output only. Error of [feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions] caused by approximation used in the explanation method. Lower value means more precise attributions. * For Sampled Shapley [attribution][google.cloud.aiplatform.v1.ExplanationParameters.sampled_shapley_attribution], increasing [path_count][google.cloud.aiplatform.v1.SampledShapleyAttribution.path_count] might reduce the error. * For Integrated Gradients [attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution], increasing [step_count][google.cloud.aiplatform.v1.IntegratedGradientsAttribution.step_count] might reduce the error. * For [XRAI attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution], increasing [step_count][google.cloud.aiplatform.v1.XraiAttribution.step_count] might reduce the error. See [this introduction](/vertex-ai/docs/explainable-ai/overview) for more information.
double approximation_error = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];String getOutputName()
Output only. Name of the explain output. Specified as the key in [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs].
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];com.google.protobuf.ByteString getOutputNameBytes()
Output only. Name of the explain output. Specified as the key in [ExplanationMetadata.outputs][google.cloud.aiplatform.v1.ExplanationMetadata.outputs].
string output_name = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];Copyright © 2024 Google LLC. All rights reserved.