Class ModelEvaluation (1.53.0)

Version 1.53.0

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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.
display_name	str The display name of the ModelEvaluation.
metrics_schema_uri	str 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 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	MutableSequence[str] All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = .
data_item_schema_uri	str Points to a YAML file stored on Google Cloud Storage describing [EvaluatedDataItemView.data_item_payload][] and EvaluatedAnnotation.data_item_payload. The schema is defined as an OpenAPI 3.0.2 `Schema Object
annotation_schema_uri	str Points to a YAML file stored on Google Cloud Storage describing [EvaluatedDataItemView.predictions][], [EvaluatedDataItemView.ground_truths][], EvaluatedAnnotation.predictions, and EvaluatedAnnotation.ground_truths. The schema is defined as an OpenAPI 3.0.2 `Schema Object
model_explanation	google.cloud.aiplatform_v1.types.ModelExplanation 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	MutableSequence[google.cloud.aiplatform_v1.types.ModelEvaluation.ModelEvaluationExplanationSpec] Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.
metadata	google.protobuf.struct_pb2.Value The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path", "row_based_metrics_path".

Classes

ModelEvaluationExplanationSpec

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

Methods

ModelEvaluation

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.