Resource: ModelEvaluation
A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.
name
string
Output only. The resource name of the ModelEvaluation.
displayName
string
The display name of the ModelEvaluation.
metricsSchemaUri
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.
Evaluation metrics of the Model. The schema of the metrics is stored in metricsSchemaUri
Output only. timestamp when this ModelEvaluation was created.
A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z"
and "2014-10-02T15:01:23.045123456Z"
.
sliceDimensions[]
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>
.
dataItemSchemaUri
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.
annotationSchemaUri
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.
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.
Describes the values of ExplanationSpec
that are used for explaining the predicted values on the evaluated data.
The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipelineJobId", "evaluation_dataset_type", "evaluation_dataset_path", "row_based_metrics_path".
JSON representation |
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{ "name": string, "displayName": string, "metricsSchemaUri": string, "metrics": value, "createTime": string, "sliceDimensions": [ string ], "dataItemSchemaUri": string, "annotationSchemaUri": string, "modelExplanation": { object ( |
ModelEvaluationExplanationSpec
explanationType
string
Explanation type.
For AutoML Image Classification models, possible values are:
image-integrated-gradients
image-xrai
Explanation spec details.
JSON representation |
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{
"explanationType": string,
"explanationSpec": {
object ( |
Methods |
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Gets a ModelEvaluation. |
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Imports an externally generated ModelEvaluation. |
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Lists ModelEvaluations in a Model. |