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.AttributeConfig

Description

Synopsis

Documentation

data AttributeConfig Source #

Provides information about the method used to transform attributes.

The following is an example using the RETAIL domain:

"AttributeName": "demand",

"Transformations": {"aggregation": "sum", "middlefill": "zero", "backfill": "zero"}

See: newAttributeConfig smart constructor.

Constructors

AttributeConfig'

Fields

attributeName :: Text
The name of the attribute as specified in the schema. Amazon Forecast supports the target field of the target time series and the related time series datasets. For example, for the RETAIL domain, the target is demand.
transformations :: HashMap Text Text
The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.
The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Default values are bolded.
- aggregation: sum, avg, first, min, max
- frontfill: none
- middlefill: zero, nan (not a number), value, median, mean, min, max
- backfill: zero, nan, value, median, mean, min, max
The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):
- middlefill: zero, value, median, mean, min, max
- backfill: zero, value, median, mean, min, max
- futurefill: zero, value, median, mean, min, max
To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".

Instances

Instances details

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

newAttributeConfig Source #

Arguments

:: Text	`$sel:attributeName:AttributeConfig'`
-> AttributeConfig

Create a value of AttributeConfig 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:attributeName:AttributeConfig', attributeConfig_attributeName - The name of the attribute as specified in the schema. Amazon Forecast supports the target field of the target time series and the related time series datasets. For example, for the RETAIL domain, the target is demand.

$sel:transformations:AttributeConfig', attributeConfig_transformations - The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.

The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Default values are bolded.

aggregation: sum, avg, first, min, max
frontfill: none
middlefill: zero, nan (not a number), value, median, mean, min, max
backfill: zero, nan, value, median, mean, min, max

The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):

middlefill: zero, value, median, mean, min, max
backfill: zero, value, median, mean, min, max
futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".

attributeConfig_attributeName :: Lens' AttributeConfig Text Source #

The name of the attribute as specified in the schema. Amazon Forecast supports the target field of the target time series and the related time series datasets. For example, for the RETAIL domain, the target is demand.

attributeConfig_transformations :: Lens' AttributeConfig (HashMap Text Text) Source #

The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.

The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Default values are bolded.

aggregation: sum, avg, first, min, max
frontfill: none
middlefill: zero, nan (not a number), value, median, mean, min, max
backfill: zero, nan, value, median, mean, min, max

The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):

middlefill: zero, value, median, mean, min, max
backfill: zero, value, median, mean, min, max
futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".