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.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

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.
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.

Instances

Instances details

Eq WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods (==) :: WeightedQuantileLoss -> WeightedQuantileLoss -> Bool # (/=) :: WeightedQuantileLoss -> WeightedQuantileLoss -> Bool #
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 #
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 #
NFData WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods rnf :: WeightedQuantileLoss -> () #
Hashable WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods hashWithSalt :: Int -> WeightedQuantileLoss -> Int # hash :: WeightedQuantileLoss -> Int #
FromJSON WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss Methods parseJSON :: Value -> Parser WeightedQuantileLoss # parseJSONList :: Value -> Parser [WeightedQuantileLoss] #
type Rep WeightedQuantileLoss Source #
Instance details Defined in Amazonka.Forecast.Types.WeightedQuantileLoss type Rep WeightedQuantileLoss = D1 ('MetaData "WeightedQuantileLoss" "Amazonka.Forecast.Types.WeightedQuantileLoss" "libZSservicesZSamazonka-forecastZSamazonka-forecast" 'False) (C1 ('MetaCons "WeightedQuantileLoss'" 'PrefixI 'True) (S1 ('MetaSel ('Just "quantile") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Double)) :*: S1 ('MetaSel ('Just "lossValue") '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: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.

$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.

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.

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.