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Class: Aws::ForecastService::Types::Featurization
- Inherits:
-
Struct
- Object
- Struct
- Aws::ForecastService::Types::Featurization
- Defined in:
- (unknown)
Overview
When passing Featurization as input to an Aws::Client method, you can use a vanilla Hash:
{
attribute_name: "Name", # required
featurization_pipeline: [
{
featurization_method_name: "filling", # required, accepts filling
featurization_method_parameters: {
"ParameterKey" => "ParameterValue",
},
},
],
}
Provides featurization (transformation) information for a dataset field. This object is part of the FeaturizationConfig object.
For example:
{
"AttributeName": "demand",
FeaturizationPipeline [ {
"FeaturizationMethodName": "filling",
"FeaturizationMethodParameters": {"aggregation": "avg", "backfill": "nan"}
} ]
}
Instance Attribute Summary collapse
-
#attribute_name ⇒ String
The name of the schema attribute that specifies the data field to be featurized.
-
#featurization_pipeline ⇒ Array<Types::FeaturizationMethod>
An array of one
FeaturizationMethod
object that specifies the feature transformation method.
Instance Attribute Details
#attribute_name ⇒ String
The name of the schema attribute that specifies the data field to be
featurized. 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
, and for the
CUSTOM
domain, the target is target_value
. For more information, see
howitworks-missing-values.
#featurization_pipeline ⇒ Array<Types::FeaturizationMethod>
An array of one FeaturizationMethod
object that specifies the feature
transformation method.