Class ModelEvaluation (1.6.2)

Version 1.6.2

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ModelEvaluation(mapping=None, *, ignore_unknown_fields=False, **kwargs)

A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.

Attributes

Name	Description
name	str Output only. The resource name of the ModelEvaluation.
metrics_schema_uri	str Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 `Schema Object
metrics	google.protobuf.struct_pb2.Value Output only. Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
create_time	google.protobuf.timestamp_pb2.Timestamp Output only. Timestamp when this ModelEvaluation was created.
slice_dimensions	Sequence[str] Output only. All possible `dimensions][ModelEvaluationSlice.slice.dimension]` of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of ``slice.dimension =
model_explanation	google.cloud.aiplatform_v1beta1.types.ModelExplanation Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.
explanation_specs	Sequence[google.cloud.aiplatform_v1beta1.types.ModelEvaluation.ModelEvaluationExplanationSpec] Output only. Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.

Inheritance

builtins.object > proto.message.Message > ModelEvaluation

Classes

ModelEvaluationExplanationSpec

ModelEvaluationExplanationSpec(
    mapping=None, *, ignore_unknown_fields=False, **kwargs
)