Releases¶

[0.3.0] - [2021-09-01]¶

cv_forecaster returns cross-validation metrics and cross-validation predictions.
Added an extra column for each parameter in the dataframe returned by grid_search_forecaster.
statsmodels 0.12.2 added to requirements

New implementation of ForecasterAutoregMultiOutput. The training process in the new version creates a different X_train for each step. See Direct multi-step forecasting for more details. Old versión can be acces with skforecast.deprecated.ForecasterAutoregMultiOutput.

Logging total number of models to fit in grid_search_forecaster.
Class ForecasterAutoregCustom.
Method create_train_X_y to facilitate access to the training data matrix created from y and exog.

New implementation of ForecasterAutoregMultiOutput. The training process in the new version creates a different X_train for each step. See Direct multi-step forecasting for more details. Old versión can be acces with skforecast.deprecated.ForecasterAutoregMultiOutput.
Class ForecasterCustom has been renamed to ForecasterAutoregCustom. However, ForecasterCustom will still remain to keep backward compatibility.
Argument metric in cv_forecaster, backtesting_forecaster, grid_search_forecaster and backtesting_forecaster_intervals changed from 'neg_mean_squared_error', 'neg_mean_absolute_error', 'neg_mean_absolute_percentage_error' to 'mean_squared_error', 'mean_absolute_error', 'mean_absolute_percentage_error'.
Check if argument metric in cv_forecaster, backtesting_forecaster, grid_search_forecaster and backtesting_forecaster_intervals is one of 'mean_squared_error', 'mean_absolute_error', 'mean_absolute_percentage_error'.
time_series_spliter doesn't include the remaining observations in the last complete fold but in a new one when allow_incomplete_fold=True. Take in consideration that incomplete folds with few observations could overestimate or underestimate the validation metric.

set_out_sample_residuals method to store or update out of sample residuals used by predict_interval.

backtesting_forecaster_intervals and backtesting_forecaster print number of steps per fold.
Only stored up to 1000 residuals.
Improved verbose in backtesting_forecaster_intervals.

Warning of inclompleted folds when using backtesting_forecast with a ForecasterAutoregMultiOutput.
ForecasterAutoregMultiOutput.predict allow exog data longer than needed (steps).
backtesting_forecast prints correctly the number of folds when remainder observations are cero.
Removed named argument X in self.regressor.predict(X) to allow using XGBoost regressor.
Values stored in self.last_window when training ForecasterAutoregMultiOutput.

Class ForecasterAutoregMultiOutput.py: forecaster with direct multi-step predictions.
Method ForecasterCustom.predict_interval and ForecasterAutoreg.predict_interval: estimate prediction interval using bootstrapping.
skforecast.model_selection.backtesting_forecaster_intervals perform backtesting and return prediction intervals.

Class ForecasterCustom: same functionalities as ForecasterAutoreg but allows custom definition of predictors.

grid_search forecaster adapted to work with objects ForecasterCustom in addition to ForecasterAutoreg.

Method create_lags return a matrix where the order of columns match the ascending order of lags. For example, column 0 contains the values of the minimum lag used as predictor.
Renamed argument X to last_window in method predict.
Renamed ts_cv_forecaster to cv_forecaster.