# Generated by default/object.tt package Paws::Forecast::FeaturizationConfig; use Moose; has Featurizations => (is => 'ro', isa => 'ArrayRef[Paws::Forecast::Featurization]'); has ForecastDimensions => (is => 'ro', isa => 'ArrayRef[Str|Undef]'); has ForecastFrequency => (is => 'ro', isa => 'Str', required => 1); 1; ### main pod documentation begin ### =head1 NAME Paws::Forecast::FeaturizationConfig =head1 USAGE This class represents one of two things: =head3 Arguments in a call to a service Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object. As an example, if Att1 is expected to be a Paws::Forecast::FeaturizationConfig object: $service_obj->Method(Att1 => { Featurizations => $value, ..., ForecastFrequency => $value }); =head3 Results returned from an API call Use accessors for each attribute. If Att1 is expected to be an Paws::Forecast::FeaturizationConfig object: $result = $service_obj->Method(...); $result->Att1->Featurizations =head1 DESCRIPTION In a CreatePredictor operation, the specified algorithm trains a model using the specified dataset group. You can optionally tell the operation to modify data fields prior to training a model. These modifications are referred to as I. You define featurization using the C object. You specify an array of transformations, one for each field that you want to featurize. You then include the C object in your C request. Amazon Forecast applies the featurization to the C and C datasets before model training. You can create multiple featurization configurations. For example, you might call the C operation twice by specifying different featurization configurations. =head1 ATTRIBUTES =head2 Featurizations => ArrayRef[L] An array of featurization (transformation) information for the fields of a dataset. =head2 ForecastDimensions => ArrayRef[Str|Undef] An array of dimension (field) names that specify how to group the generated forecast. For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a C field. If you want the sales forecast for each item by store, you would specify C as the dimension. All forecast dimensions specified in the C dataset don't need to be specified in the C request. All forecast dimensions specified in the C dataset must be specified in the C request. =head2 B ForecastFrequency => Str The frequency of predictions in a forecast. Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "Y" indicates every year and "5min" indicates every five minutes. The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency. When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency. =head1 SEE ALSO This class forms part of L, describing an object used in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut