amazonka-ml-1.3.1: Amazon Machine Learning SDK.

Copyright(c) 2013-2015 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay@gmail.com>
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellNone
LanguageHaskell2010

Network.AWS.MachineLearning.GetEvaluation

Contents

Description

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

See: AWS API Reference for GetEvaluation.

Synopsis

Creating a Request

getEvaluation Source

Creates a value of GetEvaluation with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

Request Lenses

geEvaluationId :: Lens' GetEvaluation Text Source

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.

Destructuring the Response

Response Lenses

gersStatus :: Lens' GetEvaluationResponse (Maybe EntityStatus) Source

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.

gersPerformanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics) Source

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.

gersLastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) Source

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

gersCreatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) Source

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

gersInputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text) Source

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

gersMLModelId :: Lens' GetEvaluationResponse (Maybe Text) Source

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

gersCreatedByIAMUser :: Lens' GetEvaluationResponse (Maybe Text) Source

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.

gersName :: Lens' GetEvaluationResponse (Maybe Text) Source

A user-supplied name or description of the Evaluation.

gersLogURI :: Lens' GetEvaluationResponse (Maybe Text) Source

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

gersEvaluationId :: Lens' GetEvaluationResponse (Maybe Text) Source

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

gersMessage :: Lens' GetEvaluationResponse (Maybe Text) Source

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