Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ModelEvaluation (v0.20.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ModelEvaluation.

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

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#annotation_schema_uri

def annotation_schema_uri() -> ::String
Returns
  • (::String) — 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.

    This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

#annotation_schema_uri=

def annotation_schema_uri=(value) -> ::String
Parameter
  • value (::String) — 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.

    This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

Returns
  • (::String) — 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.

    This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

#create_time

def create_time() -> ::Google::Protobuf::Timestamp
Returns

#data_item_schema_uri

def data_item_schema_uri() -> ::String
Returns
  • (::String) — 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.

    This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

#data_item_schema_uri=

def data_item_schema_uri=(value) -> ::String
Parameter
  • value (::String) — 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.

    This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

Returns
  • (::String) — 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.

    This field is not populated if there are neither EvaluatedDataItemViews nor EvaluatedAnnotations under this ModelEvaluation.

#display_name

def display_name() -> ::String
Returns
  • (::String) — The display name of the ModelEvaluation.

#display_name=

def display_name=(value) -> ::String
Parameter
  • value (::String) — The display name of the ModelEvaluation.
Returns
  • (::String) — The display name of the ModelEvaluation.

#explanation_specs

def explanation_specs() -> ::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>
Returns

#explanation_specs=

def explanation_specs=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>
Parameter
Returns

#metadata

def metadata() -> ::Google::Protobuf::Value
Returns
  • (::Google::Protobuf::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".

#metadata=

def metadata=(value) -> ::Google::Protobuf::Value
Parameter
  • value (::Google::Protobuf::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".
Returns
  • (::Google::Protobuf::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".

#metrics

def metrics() -> ::Google::Protobuf::Value
Returns

#metrics=

def metrics=(value) -> ::Google::Protobuf::Value
Parameter
Returns

#metrics_schema_uri

def metrics_schema_uri() -> ::String
Returns
  • (::String) — 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_schema_uri=

def metrics_schema_uri=(value) -> ::String
Parameter
  • value (::String) — 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.
Returns
  • (::String) — 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.

#model_explanation

def model_explanation() -> ::Google::Cloud::AIPlatform::V1::ModelExplanation
Returns
  • (::Google::Cloud::AIPlatform::V1::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.

#model_explanation=

def model_explanation=(value) -> ::Google::Cloud::AIPlatform::V1::ModelExplanation
Parameter
  • value (::Google::Cloud::AIPlatform::V1::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.
Returns
  • (::Google::Cloud::AIPlatform::V1::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.

#name

def name() -> ::String
Returns
  • (::String) — Output only. The resource name of the ModelEvaluation.

#slice_dimensions

def slice_dimensions() -> ::Array<::String>
Returns
  • (::Array<::String>) — 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 = <dimension>.

#slice_dimensions=

def slice_dimensions=(value) -> ::Array<::String>
Parameter
  • value (::Array<::String>) — 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 = <dimension>.
Returns
  • (::Array<::String>) — 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 = <dimension>.