RecursiveRegressionForecaster

class sktime.forecasting.compose.RecursiveRegressionForecaster(regressor, window_length=10, step_length=1)[source]

Forecasting based on reduction to tabular regression with a recursive reduction strategy. For the recursive reduction strategy, a single estimator is fit for a one-step-ahead forecasting horizon and then called iteratively to predict multiple steps ahead.

Parameters
  • regressor (sklearn estimator object) – Define the regression model type.

  • window_length (int, optional (default=10)) – The length of the sliding window used to transform the series into a tabular matrix

  • step_length (int, optional (default=1)) – The number of time steps taken at each step of the sliding window used to transform the series into a tabular matrix.

__init__(regressor, window_length=10, step_length=1)[source]

Initialize self. See help(type(self)) for accurate signature.