Amazon Forecast is no longer available to new customers. Existing customers of
Amazon Forecast can continue to use the service as normal.
Learn more"
EvaluationParameters
Parameters that define how to split a dataset into training data and testing data, and the number of iterations to perform. These parameters are specified in the predefined algorithms but you can override them in the CreatePredictor request.
Contents
- BackTestWindowOffset
-
The point from the end of the dataset where you want to split the data for model training and testing (evaluation). Specify the value as the number of data points. The default is the value of the forecast horizon.
BackTestWindowOffsetcan be used to mimic a past virtual forecast start date. This value must be greater than or equal to the forecast horizon and less than half of the TARGET_TIME_SERIES dataset length.ForecastHorizon<=BackTestWindowOffset< 1/2 * TARGET_TIME_SERIES dataset lengthType: Integer
Required: No
- NumberOfBacktestWindows
-
The number of times to split the input data. The default is 1. Valid values are 1 through 5.
Type: Integer
Required: No
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
