[ aws . machinelearning ]

get-evaluation

Description

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

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  get-evaluation
--evaluation-id <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--cli-auto-prompt <value>]

Options

--evaluation-id (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.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

--cli-auto-prompt (boolean) Automatically prompt for CLI input parameters.

See ‘aws help’ for descriptions of global parameters.

Output

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 -> (timestamp)

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

LastUpdatedAt -> (timestamp)

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 -> (structure)

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 -> (map)

key -> (string)

value -> (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 -> (long)

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 -> (timestamp)

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 -> (timestamp)

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