amazonka-ml-1.4.3: Amazon Machine Learning SDK.

Copyright(c) 2013-2016 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.

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:

data GetEvaluation Source #

See: getEvaluation smart constructor.

Instances

Eq GetEvaluation Source # 
Data GetEvaluation Source # 

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GetEvaluation -> c GetEvaluation #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GetEvaluation #

toConstr :: GetEvaluation -> Constr #

dataTypeOf :: GetEvaluation -> DataType #

dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c GetEvaluation) #

dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GetEvaluation) #

gmapT :: (forall b. Data b => b -> b) -> GetEvaluation -> GetEvaluation #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GetEvaluation -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GetEvaluation -> r #

gmapQ :: (forall d. Data d => d -> u) -> GetEvaluation -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GetEvaluation -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GetEvaluation -> m GetEvaluation #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GetEvaluation -> m GetEvaluation #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GetEvaluation -> m GetEvaluation #

Read GetEvaluation Source # 
Show GetEvaluation Source # 
Generic GetEvaluation Source # 

Associated Types

type Rep GetEvaluation :: * -> * #

ToJSON GetEvaluation Source # 
Hashable GetEvaluation Source # 
NFData GetEvaluation Source # 

Methods

rnf :: GetEvaluation -> () #

AWSRequest GetEvaluation Source # 
ToPath GetEvaluation Source # 
ToHeaders GetEvaluation Source # 
ToQuery GetEvaluation Source # 
type Rep GetEvaluation Source # 
type Rep GetEvaluation = D1 (MetaData "GetEvaluation" "Network.AWS.MachineLearning.GetEvaluation" "amazonka-ml-1.4.3-DbYWzKGDN8K1aNJlQiNb67" True) (C1 (MetaCons "GetEvaluation'" PrefixI True) (S1 (MetaSel (Just Symbol "_geEvaluationId") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 Text)))
type Rs GetEvaluation Source # 

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

data GetEvaluationResponse Source #

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

See: getEvaluationResponse smart constructor.

Instances

Eq GetEvaluationResponse Source # 
Data GetEvaluationResponse Source # 

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> GetEvaluationResponse -> c GetEvaluationResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c GetEvaluationResponse #

toConstr :: GetEvaluationResponse -> Constr #

dataTypeOf :: GetEvaluationResponse -> DataType #

dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c GetEvaluationResponse) #

dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c GetEvaluationResponse) #

gmapT :: (forall b. Data b => b -> b) -> GetEvaluationResponse -> GetEvaluationResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> GetEvaluationResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> GetEvaluationResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> GetEvaluationResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> GetEvaluationResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> GetEvaluationResponse -> m GetEvaluationResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> GetEvaluationResponse -> m GetEvaluationResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> GetEvaluationResponse -> m GetEvaluationResponse #

Read GetEvaluationResponse Source # 
Show GetEvaluationResponse Source # 
Generic GetEvaluationResponse Source # 
NFData GetEvaluationResponse Source # 

Methods

rnf :: GetEvaluationResponse -> () #

type Rep GetEvaluationResponse Source # 
type Rep GetEvaluationResponse = D1 (MetaData "GetEvaluationResponse" "Network.AWS.MachineLearning.GetEvaluation" "amazonka-ml-1.4.3-DbYWzKGDN8K1aNJlQiNb67" False) (C1 (MetaCons "GetEvaluationResponse'" PrefixI True) ((:*:) ((:*:) ((:*:) (S1 (MetaSel (Just Symbol "_gersStatus") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe EntityStatus))) ((:*:) (S1 (MetaSel (Just Symbol "_gersPerformanceMetrics") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe PerformanceMetrics))) (S1 (MetaSel (Just Symbol "_gersLastUpdatedAt") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe POSIX))))) ((:*:) (S1 (MetaSel (Just Symbol "_gersCreatedAt") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe POSIX))) ((:*:) (S1 (MetaSel (Just Symbol "_gersInputDataLocationS3") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) (S1 (MetaSel (Just Symbol "_gersMLModelId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))))) ((:*:) ((:*:) (S1 (MetaSel (Just Symbol "_gersCreatedByIAMUser") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) ((:*:) (S1 (MetaSel (Just Symbol "_gersName") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) (S1 (MetaSel (Just Symbol "_gersLogURI") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))))) ((:*:) ((:*:) (S1 (MetaSel (Just Symbol "_gersEvaluationId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) (S1 (MetaSel (Just Symbol "_gersMessage") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text)))) ((:*:) (S1 (MetaSel (Just Symbol "_gersEvaluationDataSourceId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Maybe Text))) (S1 (MetaSel (Just Symbol "_gersResponseStatus") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 Int)))))))

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.