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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
- (::Google::Protobuf::Timestamp) — Output only. Timestamp when this ModelEvaluation was created.
#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.
#explanation_specs
def explanation_specs() -> ::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>
Returns
- (::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>) — Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.
#explanation_specs=
def explanation_specs=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>
Parameter
- value (::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>) — Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.
Returns
- (::Array<::Google::Cloud::AIPlatform::V1::ModelEvaluation::ModelEvaluationExplanationSpec>) — Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.
#metrics
def metrics() -> ::Google::Protobuf::Value
Returns
- (::Google::Protobuf::Value) — Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
#metrics=
def metrics=(value) -> ::Google::Protobuf::Value
Parameter
- value (::Google::Protobuf::Value) — Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
Returns
- (::Google::Protobuf::Value) — Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
#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>.