amazonka-ml-1.6.0: Amazon Machine Learning SDK.

Copyright(c) 2013-2018 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay+amazonka@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:

  • geEvaluationId - 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.

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 :: * -> * #

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

Methods

rnf :: GetEvaluation -> () #

AWSRequest GetEvaluation Source # 
ToHeaders GetEvaluation Source # 
ToPath GetEvaluation Source # 
ToQuery GetEvaluation Source # 
type Rep GetEvaluation Source # 
type Rep GetEvaluation = D1 * (MetaData "GetEvaluation" "Network.AWS.MachineLearning.GetEvaluation" "amazonka-ml-1.6.0-Ieesuz5Kri8FW4cNPxVPkB" 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

getEvaluationResponse Source #

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

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

  • gersStatus - 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 - 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 - The time of the most recent edit to the Evaluation . The time is expressed in epoch time.
  • gersCreatedAt - The time that the Evaluation was created. The time is expressed in epoch time.
  • gersComputeTime - 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.
  • gersInputDataLocationS3 - The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
  • gersMLModelId - The ID of the MLModel that was the focus of the evaluation.
  • gersStartedAt - The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS . StartedAt isn't available if the Evaluation is in the PENDING state.
  • gersFinishedAt - 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.
  • gersCreatedByIAMUser - 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 - A user-supplied name or description of the Evaluation .
  • gersLogURI - A link to the file that contains logs of the CreateEvaluation operation.
  • gersEvaluationId - The evaluation ID which is same as the EvaluationId in the request.
  • gersMessage - A description of the most recent details about evaluating the MLModel .
  • gersEvaluationDataSourceId - The DataSource used for this evaluation.
  • gersResponseStatus - -- | The response status code.

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-1.6.0-Ieesuz5Kri8FW4cNPxVPkB" 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 "_gersComputeTime") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 * (Maybe Integer))) (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 "_gersStartedAt") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 * (Maybe POSIX)))))) ((:*:) * ((:*:) * ((:*:) * (S1 * (MetaSel (Just Symbol "_gersFinishedAt") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 * (Maybe POSIX))) (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 Evaluation . 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.

gersComputeTime :: Lens' GetEvaluationResponse (Maybe Integer) Source #

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.

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.

gersStartedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) Source #

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

gersFinishedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) Source #

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.

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 .

gersEvaluationDataSourceId :: Lens' GetEvaluationResponse (Maybe Text) Source #

The DataSource used for this evaluation.

gersResponseStatus :: Lens' GetEvaluationResponse Int Source #

  • - | The response status code.