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# FeaturizationConfig
**Note**
This object belongs to the [CreatePredictor](API_CreatePredictor.md) operation. If you created your predictor with [CreateAutoPredictor](API_CreateAutoPredictor.md), see [AttributeConfig](API_AttributeConfig.md).
In a [CreatePredictor](API_CreatePredictor.md) 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 *featurization*.
You define featurization using the `FeaturizationConfig` object. You specify an array of transformations, one for each field that you want to featurize. You then include the `FeaturizationConfig` object in your `CreatePredictor` request. Amazon Forecast applies the featurization to the `TARGET_TIME_SERIES` and `RELATED_TIME_SERIES` datasets before model training.
You can create multiple featurization configurations. For example, you might call the `CreatePredictor` operation twice by specifying different featurization configurations.
## Contents
** ForecastFrequency **
The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
+ Minute - 1-59
+ Hour - 1-23
+ Day - 1-6
+ Week - 1-4
+ Month - 1-11
+ Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
The frequency must be greater than or equal to the TARGET\$1TIME\$1SERIES dataset frequency.
When a RELATED\$1TIME\$1SERIES dataset is provided, the frequency must be equal to the TARGET\$1TIME\$1SERIES dataset frequency.
Type: String
Length Constraints: Minimum length of 1. Maximum length of 5.
Pattern: `^Y|M|W|D|H|30min|15min|10min|5min|1min$`
Required: Yes
** Featurizations **
An array of featurization (transformation) information for the fields of a dataset.
Type: Array of [Featurization](API_Featurization.md) objects
Array Members: Minimum number of 1 item. Maximum number of 50 items.
Required: No
** ForecastDimensions **
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 `store_id` field. If you want the sales forecast for each item by store, you would specify `store_id` as the dimension.
All forecast dimensions specified in the `TARGET_TIME_SERIES` dataset don't need to be specified in the `CreatePredictor` request. All forecast dimensions specified in the `RELATED_TIME_SERIES` dataset must be specified in the `CreatePredictor` request.
Type: Array of strings
Array Members: Minimum number of 1 item. Maximum number of 10 items.
Length Constraints: Minimum length of 1. Maximum length of 63.
Pattern: `^[a-zA-Z][a-zA-Z0-9_]*`
Required: No
## See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
+ [AWS SDK for C\$1\$1](https://docs.aws.amazon.com/goto/SdkForCpp/forecast-2018-06-26/FeaturizationConfig)
+ [AWS SDK for Java V2](https://docs.aws.amazon.com/goto/SdkForJavaV2/forecast-2018-06-26/FeaturizationConfig)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/forecast-2018-06-26/FeaturizationConfig)