Copyright	(c) 2013-2021 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay <brendan.g.hay+amazonka@gmail.com>
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	None

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

Eq GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods (==) :: GetAccuracyMetrics -> GetAccuracyMetrics -> Bool # (/=) :: GetAccuracyMetrics -> GetAccuracyMetrics -> Bool #
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 #
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 #
NFData GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods rnf :: GetAccuracyMetrics -> () #
Hashable GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods hashWithSalt :: Int -> GetAccuracyMetrics -> Int # hash :: GetAccuracyMetrics -> Int #
ToJSON GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods toJSON :: GetAccuracyMetrics -> Value # toEncoding :: GetAccuracyMetrics -> Encoding # toJSONList :: [GetAccuracyMetrics] -> Value # toEncodingList :: [GetAccuracyMetrics] -> Encoding #
AWSRequest GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Associated Types type AWSResponse GetAccuracyMetrics # Methods request :: GetAccuracyMetrics -> Request GetAccuracyMetrics # response :: MonadResource m => Logger -> Service -> Proxy GetAccuracyMetrics -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse GetAccuracyMetrics))) #
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 #
type Rep GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics type Rep GetAccuracyMetrics = D1 ('MetaData "GetAccuracyMetrics" "Amazonka.Forecast.GetAccuracyMetrics" "libZSservicesZSamazonka-forecastZSamazonka-forecast" 'False) (C1 ('MetaCons "GetAccuracyMetrics'" 'PrefixI 'True) (S1 ('MetaSel ('Just "predictorArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text)))
type AWSResponse GetAccuracyMetrics Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics type AWSResponse GetAccuracyMetrics = GetAccuracyMetricsResponse

newGetAccuracyMetrics Source #

Arguments

:: Text	`$sel:predictorArn: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:

$sel:predictorArn: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

predictorEvaluationResults :: Maybe [EvaluationResult]
An array of results from evaluating the predictor.
optimizationMetric :: Maybe OptimizationMetric
The accuracy metric used to optimize the predictor.
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.
httpStatus :: Int
The response's http status code.

Instances

Instances details

Eq GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods (==) :: GetAccuracyMetricsResponse -> GetAccuracyMetricsResponse -> Bool # (/=) :: GetAccuracyMetricsResponse -> GetAccuracyMetricsResponse -> Bool #
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 #
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 #
NFData GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics Methods rnf :: GetAccuracyMetricsResponse -> () #
type Rep GetAccuracyMetricsResponse Source #
Instance details Defined in Amazonka.Forecast.GetAccuracyMetrics type Rep GetAccuracyMetricsResponse = D1 ('MetaData "GetAccuracyMetricsResponse" "Amazonka.Forecast.GetAccuracyMetrics" "libZSservicesZSamazonka-forecastZSamazonka-forecast" 'False) (C1 ('MetaCons "GetAccuracyMetricsResponse'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "predictorEvaluationResults") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [EvaluationResult])) :: S1 ('MetaSel ('Just "optimizationMetric") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe OptimizationMetric))) :: (S1 ('MetaSel ('Just "autoMLOverrideStrategy") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe AutoMLOverrideStrategy)) :*: 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:predictorEvaluationResults:GetAccuracyMetricsResponse', getAccuracyMetricsResponse_predictorEvaluationResults - An array of results from evaluating the predictor.

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

$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.

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

Response Lenses

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

An array of results from evaluating the predictor.

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

The accuracy metric used to optimize the predictor.

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_httpStatus :: Lens' GetAccuracyMetricsResponse Int Source #

The response's http status code.