Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ModelEvaluation (v0.35.0)

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

(::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.

#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

(::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.

#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

(::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 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 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 of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of slice.dimension = <dimension>.