Returns an Evaluation that includes metadata as well as the current status of the Evaluation .

See also: AWS API Documentation

Request Syntax

response = client.get_evaluation(
EvaluationId (string) --


The ID of the Evaluation to retrieve. The evaluation of each MLModel is recorded and cataloged. The ID provides the means to access the information.

Return type
Response Syntax
    'EvaluationId': 'string',
    'MLModelId': 'string',
    'EvaluationDataSourceId': 'string',
    'InputDataLocationS3': 'string',
    'CreatedByIamUser': 'string',
    'CreatedAt': datetime(2015, 1, 1),
    'LastUpdatedAt': datetime(2015, 1, 1),
    'Name': 'string',
    'PerformanceMetrics': {
        'Properties': {
            'string': 'string'
    'LogUri': 'string',
    'Message': 'string',
    'ComputeTime': 123,
    'FinishedAt': datetime(2015, 1, 1),
    'StartedAt': datetime(2015, 1, 1)

Response Structure

  • (dict) --

    Represents the output of a GetEvaluation operation and describes an Evaluation .

    • EvaluationId (string) --

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

    • MLModelId (string) --

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

    • EvaluationDataSourceId (string) --

      The DataSource used for this evaluation.

    • InputDataLocationS3 (string) --

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

    • CreatedByIamUser (string) --

      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.

    • CreatedAt (datetime) --

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

    • LastUpdatedAt (datetime) --

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

    • Name (string) --

      A user-supplied name or description of the Evaluation .

    • Status (string) --

      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.
    • PerformanceMetrics (dict) --

      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.

      • Properties (dict) --
        • (string) --
          • (string) --
    • LogUri (string) --

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

    • Message (string) --

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

    • ComputeTime (integer) --

      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.

    • FinishedAt (datetime) --

      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.

    • StartedAt (datetime) --

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


  • MachineLearning.Client.exceptions.InvalidInputException
  • MachineLearning.Client.exceptions.ResourceNotFoundException
  • MachineLearning.Client.exceptions.InternalServerException