Copyright	(c) 2013-2023 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	Safe-Inferred
Language	Haskell2010

Amazonka.Forecast.GetAccuracyMetrics

Contents

Creating a Request
Request Lenses
Destructuring the Response
Response Lenses

Description

Provides metrics on the accuracy of the models that were trained by the CreatePredictor operation. Use metrics to see how well the model performed and to decide whether to use the predictor to generate a forecast. For more information, see Predictor Metrics.

This operation generates metrics for each backtest window that was evaluated. The number of backtest windows (NumberOfBacktestWindows) is specified using the EvaluationParameters object, which is optionally included in the CreatePredictor request. If NumberOfBacktestWindows isn't specified, the number defaults to one.

The parameters of the filling method determine which items contribute to the metrics. If you want all items to contribute, specify zero. If you want only those items that have complete data in the range being evaluated to contribute, specify nan. For more information, see FeaturizationMethod.

Before you can get accuracy metrics, the Status of the predictor must be ACTIVE, signifying that training has completed. To get the status, use the DescribePredictor operation.

Synopsis

Creating a Request

data GetAccuracyMetrics Source #

See: newGetAccuracyMetrics smart constructor.

Constructors

GetAccuracyMetrics'
Fields predictorArn :: Text The Amazon Resource Name (ARN) of the predictor to get metrics for.

Instances

Instances details

ToJSON GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods toJSON :: GetAccuracyMetrics -> Value # toEncoding :: GetAccuracyMetrics -> Encoding # toJSONList :: [GetAccuracyMetrics] -> Value # toEncodingList :: [GetAccuracyMetrics] -> Encoding #
ToHeaders GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods toHeaders :: GetAccuracyMetrics -> [Header] #
ToPath GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods toPath :: GetAccuracyMetrics -> ByteString #
ToQuery GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods toQuery :: GetAccuracyMetrics -> QueryString #
AWSRequest GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Associated Types type AWSResponse GetAccuracyMetrics # Methods request :: (Service -> Service) -> GetAccuracyMetrics -> Request GetAccuracyMetrics # response :: MonadResource m => (ByteStringLazy -> IO ByteStringLazy) -> Service -> Proxy GetAccuracyMetrics -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse GetAccuracyMetrics))) #
Generic GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Associated Types type Rep GetAccuracyMetrics :: Type -> Type # Methods from :: GetAccuracyMetrics -> Rep GetAccuracyMetrics x # to :: Rep GetAccuracyMetrics x -> GetAccuracyMetrics #
Read GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods readsPrec :: Int -> ReadS GetAccuracyMetrics # readList :: ReadS [GetAccuracyMetrics] # readPrec :: ReadPrec GetAccuracyMetrics # readListPrec :: ReadPrec [GetAccuracyMetrics] #
Show GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods showsPrec :: Int -> GetAccuracyMetrics -> ShowS # show :: GetAccuracyMetrics -> String # showList :: [GetAccuracyMetrics] -> ShowS #
NFData GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods rnf :: GetAccuracyMetrics -> () #
Eq GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods (==) :: GetAccuracyMetrics -> GetAccuracyMetrics -> Bool # (/=) :: GetAccuracyMetrics -> GetAccuracyMetrics -> Bool #
Hashable GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods hashWithSalt :: Int -> GetAccuracyMetrics -> Int # hash :: GetAccuracyMetrics -> Int #
type AWSResponse GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics type AWSResponse GetAccuracyMetrics = GetAccuracyMetricsResponse
type Rep GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics type Rep GetAccuracyMetrics = D1 ('MetaData "GetAccuracyMetrics" "Amazonka.Forecast.GetAccuracyMetrics" "amazonka-forecast-2.0-HHvJwvxGrDPBJtUcnmLBqf" 'False) (C1 ('MetaCons "GetAccuracyMetrics'" 'PrefixI 'True) (S1 ('MetaSel ('Just "predictorArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text)))

newGetAccuracyMetrics Source #

Arguments

:: Text	`GetAccuracyMetrics`
-> GetAccuracyMetrics

Create a value of GetAccuracyMetrics with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

GetAccuracyMetrics, getAccuracyMetrics_predictorArn - The Amazon Resource Name (ARN) of the predictor to get metrics for.

Request Lenses

getAccuracyMetrics_predictorArn :: Lens' GetAccuracyMetrics Text Source #

The Amazon Resource Name (ARN) of the predictor to get metrics for.

Destructuring the Response

data GetAccuracyMetricsResponse Source #

See: newGetAccuracyMetricsResponse smart constructor.

Constructors

GetAccuracyMetricsResponse'

Fields

autoMLOverrideStrategy :: Maybe AutoMLOverrideStrategy
The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.
The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.
This parameter is only valid for predictors trained using AutoML.
isAutoPredictor :: Maybe Bool
Whether the predictor was created with CreateAutoPredictor.
optimizationMetric :: Maybe OptimizationMetric
The accuracy metric used to optimize the predictor.
predictorEvaluationResults :: Maybe [EvaluationResult]
An array of results from evaluating the predictor.
httpStatus :: Int
The response's http status code.

Instances

Instances details

Generic GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Associated Types type Rep GetAccuracyMetricsResponse :: Type -> Type # Methods from :: GetAccuracyMetricsResponse -> Rep GetAccuracyMetricsResponse x # to :: Rep GetAccuracyMetricsResponse x -> GetAccuracyMetricsResponse #
Read GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods readsPrec :: Int -> ReadS GetAccuracyMetricsResponse # readList :: ReadS [GetAccuracyMetricsResponse] # readPrec :: ReadPrec GetAccuracyMetricsResponse # readListPrec :: ReadPrec [GetAccuracyMetricsResponse] #
Show GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods showsPrec :: Int -> GetAccuracyMetricsResponse -> ShowS # show :: GetAccuracyMetricsResponse -> String # showList :: [GetAccuracyMetricsResponse] -> ShowS #
NFData GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods rnf :: GetAccuracyMetricsResponse -> () #
Eq GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods (==) :: GetAccuracyMetricsResponse -> GetAccuracyMetricsResponse -> Bool # (/=) :: GetAccuracyMetricsResponse -> GetAccuracyMetricsResponse -> Bool #
type Rep GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics type Rep GetAccuracyMetricsResponse = D1 ('MetaData "GetAccuracyMetricsResponse" "Amazonka.Forecast.GetAccuracyMetrics" "amazonka-forecast-2.0-HHvJwvxGrDPBJtUcnmLBqf" 'False) (C1 ('MetaCons "GetAccuracyMetricsResponse'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "autoMLOverrideStrategy") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe AutoMLOverrideStrategy)) :: S1 ('MetaSel ('Just "isAutoPredictor") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Bool))) :: (S1 ('MetaSel ('Just "optimizationMetric") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe OptimizationMetric)) :: (S1 ('MetaSel ('Just "predictorEvaluationResults") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [EvaluationResult])) :: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int)))))

newGetAccuracyMetricsResponse Source #

Arguments

:: Int	`$sel:httpStatus:GetAccuracyMetricsResponse'`
-> GetAccuracyMetricsResponse

Create a value of GetAccuracyMetricsResponse with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:autoMLOverrideStrategy:GetAccuracyMetricsResponse', getAccuracyMetricsResponse_autoMLOverrideStrategy - The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

GetAccuracyMetricsResponse, getAccuracyMetricsResponse_isAutoPredictor - Whether the predictor was created with CreateAutoPredictor.

$sel:optimizationMetric:GetAccuracyMetricsResponse', getAccuracyMetricsResponse_optimizationMetric - The accuracy metric used to optimize the predictor.

$sel:predictorEvaluationResults:GetAccuracyMetricsResponse', getAccuracyMetricsResponse_predictorEvaluationResults - An array of results from evaluating the predictor.

$sel:httpStatus:GetAccuracyMetricsResponse', getAccuracyMetricsResponse_httpStatus - The response's http status code.

Response Lenses

getAccuracyMetricsResponse_autoMLOverrideStrategy :: Lens' GetAccuracyMetricsResponse (Maybe AutoMLOverrideStrategy) Source #

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

getAccuracyMetricsResponse_isAutoPredictor :: Lens' GetAccuracyMetricsResponse (Maybe Bool) Source #

Whether the predictor was created with CreateAutoPredictor.

getAccuracyMetricsResponse_optimizationMetric :: Lens' GetAccuracyMetricsResponse (Maybe OptimizationMetric) Source #

The accuracy metric used to optimize the predictor.

getAccuracyMetricsResponse_predictorEvaluationResults :: Lens' GetAccuracyMetricsResponse (Maybe [EvaluationResult]) Source #

An array of results from evaluating the predictor.

getAccuracyMetricsResponse_httpStatus :: Lens' GetAccuracyMetricsResponse Int Source #

The response's http status code.