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Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ModelEvaluation.
A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.
Generated from protobuf message google.cloud.aiplatform.v1.ModelEvaluation
Methods
__construct
Constructor.
data
array
Optional. Data for populating the Message object.
↳ name
string
Output only. The resource name of the ModelEvaluation.
↳ display_name
string
The display name of the ModelEvaluation.
↳ metrics_schema_uri
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
Google\Protobuf\Value
Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
↳ create_time
↳ slice_dimensions
array
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>
.
↳ data_item_schema_uri
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.
↳ annotation_schema_uri
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.
↳ model_explanation
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.
↳ explanation_specs
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
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".
getName
Output only. The resource name of the ModelEvaluation.
string
setName
Output only. The resource name of the ModelEvaluation.
var
string
$this
getDisplayName
The display name of the ModelEvaluation.
string
setDisplayName
The display name of the ModelEvaluation.
var
string
$this
getMetricsSchemaUri
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 .
string
setMetricsSchemaUri
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 .
var
string
$this
getMetrics
Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
hasMetrics
clearMetrics
setMetrics
Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri
$this
getCreateTime
Output only. Timestamp when this ModelEvaluation was created.
hasCreateTime
clearCreateTime
setCreateTime
Output only. Timestamp when this ModelEvaluation was created.
$this
getSliceDimensions
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>
.
setSliceDimensions
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>
.
var
string[]
$this
getDataItemSchemaUri
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.
string
setDataItemSchemaUri
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.
var
string
$this
getAnnotationSchemaUri
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.
string
setAnnotationSchemaUri
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.
var
string
$this
getModelExplanation
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.
hasModelExplanation
clearModelExplanation
setModelExplanation
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.
$this
getExplanationSpecs
Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.
setExplanationSpecs
Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data.
$this
getMetadata
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".
hasMetadata
clearMetadata
setMetadata
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".
$this
