ReducedForecaster

class sktime.forecasting.compose.ReducedForecaster(regressor, scitype, strategy='recursive', window_length=10, step_length=1)[source]

Forecasting based on reduction

When fitting, a rolling window approach is used to first transform the target series into panel data which is then used to train a regressor. During prediction, the last available data is used as input to the fitted regressors to make forecasts.

Parameters
  • scitype (str) – Can be ‘regressor’ or ‘ts-regressor’

  • strategy (str {"direct", "recursive", "multioutput"}, optional) – Strategy to generate predictions

  • window_length (int, optional (default=10)) –

  • step_length (int, optional (default=1)) –

  • regressor (a regressor of type given by parameter scitype) –

References

..[1] Bontempi, Gianluca & Ben Taieb, Souhaib & Le Borgne, Yann-Aël. ( 2013).

Machine Learning Strategies for Time Series Forecasting.

__init__(**kwargs)[source]

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