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[ aws . machinelearning ]

create-evaluation

Description

Creates a new Evaluation of an MLModel . An MLModel is evaluated on a set of observations associated to a DataSource . Like a DataSource for an MLModel , the DataSource for an Evaluation contains values for the Target Variable . The Evaluation compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel functions on the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType : BINARY , REGRESSION or MULTICLASS .

CreateEvaluation is an asynchronous operation. In response to CreateEvaluation , Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to PENDING . After the Evaluation is created and ready for use, Amazon ML sets the status to COMPLETED .

You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  create-evaluation
--evaluation-id <value>
[--evaluation-name <value>]
--ml-model-id <value>
--evaluation-data-source-id <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--evaluation-id (string)

A user-supplied ID that uniquely identifies the Evaluation .

--evaluation-name (string)

A user-supplied name or description of the Evaluation .

--ml-model-id (string)

The ID of the MLModel to evaluate.

The schema used in creating the MLModel must match the schema of the DataSource used in the Evaluation .

--evaluation-data-source-id (string)

The ID of the DataSource for the evaluation. The schema of the DataSource must match the schema used to create the MLModel .

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI 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.

--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. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

EvaluationId -> (string)

The user-supplied ID that uniquely identifies the Evaluation . This value should be identical to the value of the EvaluationId in the request.