ForeTiS.preprocess.StatisticalFeatures

Module Contents

Functions

add_lagged_statistics(seasonal_periods, ...)

Function adding lagged and seasonal-lagged features to dataset

add_current_statistics(seasonal_periods, ...)

Function adding rolling seasonal statistics
ForeTiS.preprocess.StatisticalFeatures.add_lagged_statistics(seasonal_periods, windowsize_lagged_statistics, seasonal_lags, df, columns_for_lags_rolling_mean)

Function adding lagged and seasonal-lagged features to dataset

Parameters:

  • seasonal_periods (int) – seasonal_period used for seasonal-lagged features

  • windowsize_lagged_statistics (int) – size of window used for sales statistics

  • seasonal_lags (int) – seasonal lags to add of the features specified

  • df (pandas.DataFrame) – dataset for adding features

  • columns_for_lags_rolling_mean (list) – the columns where seasonal lagged rolling mean should be applied

ForeTiS.preprocess.StatisticalFeatures.add_current_statistics(seasonal_periods, windowsize_current_statistics, df, columns_for_rolling_mean, columns_for_lags)

Function adding rolling seasonal statistics

Parameters:

  • seasonal_periods (int) – seasonal_period used for seasonal rolling statistics

  • windowsize_current_statistics (int) – size of window used for feature statistics

  • df (pandas.DataFrame) – dataset for adding features

  • columns_for_rolling_mean (list) – the columns where the rolling mean should be applied

  • columns_for_lags (list) – the columns that should be lagged by one sample