Class: Aws::ForecastService::Types::EvaluationParameters

Inherits:

Struct

Object
Struct
Aws::ForecastService::Types::EvaluationParameters

show all

Includes:: Structure

Defined in:: 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

Returns:

(Integer)

# File '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.