@aws-sdk/client-machine-learning

GetEvaluationCommandOutput Interface

The output of GetEvaluationCommand.

Members

Name
Type
Details
$metadata RequiredResponseMetadata
Metadata pertaining to this request.
ComputeTime number | undefined

The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the Evaluation, normalized and scaled on computation resources. ComputeTime is only available if the Evaluation is in the COMPLETED state.

CreatedAt Date | undefined

The time that the Evaluation was created. The time is expressed in epoch time.

CreatedByIamUser string | undefined

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

EvaluationDataSourceId string | undefined

The DataSource used for this evaluation.

EvaluationId string | undefined

The evaluation ID which is same as the EvaluationId in the request.

FinishedAt Date | undefined

The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED or FAILED state.

InputDataLocationS3 string | undefined

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

LastUpdatedAt Date | undefined

The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

LogUri string | undefined

A link to the file that contains logs of the CreateEvaluation operation.

MLModelId string | undefined

The ID of the MLModel that was the focus of the evaluation.

Message string | undefined

A description of the most recent details about evaluating the MLModel.

Name string | undefined

A user-supplied name or description of the Evaluation.

PerformanceMetrics PerformanceMetrics | undefined

Measurements of how well the MLModel performed using observations referenced by the DataSource. One of the following metric is returned based on the type of the MLModel:

  • BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

  • RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

  • MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide .

StartedAt Date | undefined

The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. StartedAt isn't available if the Evaluation is in the PENDING state.

Status EntityStatus | undefined

The status of the evaluation. This element can have one of the following values:

  • PENDING - Amazon Machine Language (Amazon ML) submitted a request to evaluate an MLModel.

  • INPROGRESS - The evaluation is underway.

  • FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.

  • COMPLETED - The evaluation process completed successfully.

  • DELETED - The Evaluation is marked as deleted. It is not usable.

Full Signature

export interface GetEvaluationCommandOutput extends GetEvaluationOutput, MetadataBearer