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.SageMaker.Types.AutoMLCandidateGenerationConfig

Description

Synopsis

data AutoMLCandidateGenerationConfig = AutoMLCandidateGenerationConfig' {
- featureSpecificationS3Uri :: Maybe Text
}
newAutoMLCandidateGenerationConfig :: AutoMLCandidateGenerationConfig
autoMLCandidateGenerationConfig_featureSpecificationS3Uri :: Lens' AutoMLCandidateGenerationConfig (Maybe Text)

Documentation

data AutoMLCandidateGenerationConfig Source #

Stores the config information for how a candidate is generated (optional).

See: newAutoMLCandidateGenerationConfig smart constructor.

Constructors

AutoMLCandidateGenerationConfig'

Fields

featureSpecificationS3Uri :: Maybe Text
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
```
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
```
These column keys may not include the target column.
In ensembling mode, Autopilot will only support the following data types: numeric, categorical, text and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] is case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.

Instances

Instances details

FromJSON AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods parseJSON :: Value -> Parser AutoMLCandidateGenerationConfig # parseJSONList :: Value -> Parser [AutoMLCandidateGenerationConfig] #
ToJSON AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods toJSON :: AutoMLCandidateGenerationConfig -> Value # toEncoding :: AutoMLCandidateGenerationConfig -> Encoding # toJSONList :: [AutoMLCandidateGenerationConfig] -> Value # toEncodingList :: [AutoMLCandidateGenerationConfig] -> Encoding #
Generic AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Associated Types type Rep AutoMLCandidateGenerationConfig :: Type -> Type # Methods from :: AutoMLCandidateGenerationConfig -> Rep AutoMLCandidateGenerationConfig x # to :: Rep AutoMLCandidateGenerationConfig x -> AutoMLCandidateGenerationConfig #
Read AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods readsPrec :: Int -> ReadS AutoMLCandidateGenerationConfig # readList :: ReadS [AutoMLCandidateGenerationConfig] # readPrec :: ReadPrec AutoMLCandidateGenerationConfig # readListPrec :: ReadPrec [AutoMLCandidateGenerationConfig] #
Show AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods showsPrec :: Int -> AutoMLCandidateGenerationConfig -> ShowS # show :: AutoMLCandidateGenerationConfig -> String # showList :: [AutoMLCandidateGenerationConfig] -> ShowS #
NFData AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods rnf :: AutoMLCandidateGenerationConfig -> () #
Eq AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods (==) :: AutoMLCandidateGenerationConfig -> AutoMLCandidateGenerationConfig -> Bool # (/=) :: AutoMLCandidateGenerationConfig -> AutoMLCandidateGenerationConfig -> Bool #
Hashable AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig Methods hashWithSalt :: Int -> AutoMLCandidateGenerationConfig -> Int # hash :: AutoMLCandidateGenerationConfig -> Int #
type Rep AutoMLCandidateGenerationConfig Source #
Instance details Defined in Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig type Rep AutoMLCandidateGenerationConfig = D1 ('MetaData "AutoMLCandidateGenerationConfig" "Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "AutoMLCandidateGenerationConfig'" 'PrefixI 'True) (S1 ('MetaSel ('Just "featureSpecificationS3Uri") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))))

newAutoMLCandidateGenerationConfig :: AutoMLCandidateGenerationConfig Source #

Create a value of AutoMLCandidateGenerationConfig 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:featureSpecificationS3Uri:AutoMLCandidateGenerationConfig', autoMLCandidateGenerationConfig_featureSpecificationS3Uri - A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:

{ "FeatureAttributeNames":["col1", "col2", ...] }.

You can also specify the data type of the feature (optional) in the format shown below:

{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }

These column keys may not include the target column.

In ensembling mode, Autopilot will only support the following data types: numeric, categorical, text and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime and sequence.

If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.

If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.

The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] is case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.

autoMLCandidateGenerationConfig_featureSpecificationS3Uri :: Lens' AutoMLCandidateGenerationConfig (Maybe Text) Source #

A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below: