Class: Aws::ForecastService::Types::EvaluationParameters
- Inherits:
-
Struct
- Object
- Struct
- Aws::ForecastService::Types::EvaluationParameters
- Defined in:
- gems/aws-sdk-forecastservice/lib/aws-sdk-forecastservice/types.rb
Overview
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.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#back_test_window_offset ⇒ Integer
The point from the end of the dataset where you want to split the data for model training and testing (evaluation).
-
#number_of_backtest_windows ⇒ Integer
The number of times to split the input data.
Instance Attribute Details
#back_test_window_offset ⇒ Integer
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. BackTestWindowOffset
can 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 length
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# File 'gems/aws-sdk-forecastservice/lib/aws-sdk-forecastservice/types.rb', line 3876 class EvaluationParameters < Struct.new( :number_of_backtest_windows, :back_test_window_offset) SENSITIVE = [] include Aws::Structure end |
#number_of_backtest_windows ⇒ Integer
The number of times to split the input data. The default is 1. Valid values are 1 through 5.
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# File 'gems/aws-sdk-forecastservice/lib/aws-sdk-forecastservice/types.rb', line 3876 class EvaluationParameters < Struct.new( :number_of_backtest_windows, :back_test_window_offset) SENSITIVE = [] include Aws::Structure end |