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.
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).
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).
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.
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.
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.
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.
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.
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.
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).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-01-27 UTC."],[],[]]
