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.Types.WeightedQuantileLoss

Description

Documentation

data WeightedQuantileLoss Source #

The weighted loss value for a quantile. This object is part of the Metrics object.

See: newWeightedQuantileLoss smart constructor.

Constructors

WeightedQuantileLoss'

Fields

lossValue :: Maybe Double
The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.
quantile :: Maybe Double
The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

Instances

Instances details

FromJSON WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods parseJSON :: Value -> Parser WeightedQuantileLoss # parseJSONList :: Value -> Parser [WeightedQuantileLoss] #
Generic WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Associated Types type Rep WeightedQuantileLoss :: Type -> Type # Methods from :: WeightedQuantileLoss -> Rep WeightedQuantileLoss x # to :: Rep WeightedQuantileLoss x -> WeightedQuantileLoss #
Read WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods readsPrec :: Int -> ReadS WeightedQuantileLoss # readList :: ReadS [WeightedQuantileLoss] # readPrec :: ReadPrec WeightedQuantileLoss # readListPrec :: ReadPrec [WeightedQuantileLoss] #
Show WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods showsPrec :: Int -> WeightedQuantileLoss -> ShowS # show :: WeightedQuantileLoss -> String # showList :: [WeightedQuantileLoss] -> ShowS #
NFData WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods rnf :: WeightedQuantileLoss -> () #
Eq WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods (==) :: WeightedQuantileLoss -> WeightedQuantileLoss -> Bool # (/=) :: WeightedQuantileLoss -> WeightedQuantileLoss -> Bool #
Hashable WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods hashWithSalt :: Int -> WeightedQuantileLoss -> Int # hash :: WeightedQuantileLoss -> Int #
type Rep WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss type Rep WeightedQuantileLoss = D1 ('MetaData "WeightedQuantileLoss" "Amazonka.Forecast.Types.WeightedQuantileLoss" "amazonka-forecast-2.0-HHvJwvxGrDPBJtUcnmLBqf" 'False) (C1 ('MetaCons "WeightedQuantileLoss'" 'PrefixI 'True) (S1 ('MetaSel ('Just "lossValue") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :*: S1 ('MetaSel ('Just "quantile") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double))))

newWeightedQuantileLoss :: WeightedQuantileLoss Source #

Create a value of WeightedQuantileLoss 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:lossValue:WeightedQuantileLoss', weightedQuantileLoss_lossValue - The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

$sel:quantile:WeightedQuantileLoss', weightedQuantileLoss_quantile - The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

weightedQuantileLoss_lossValue :: Lens' WeightedQuantileLoss (Maybe Double) Source #

The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

weightedQuantileLoss_quantile :: Lens' WeightedQuantileLoss (Maybe Double) Source #

The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.