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changelog.md

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Change Log

All notable changes to this project will be documented in this file.

[0.1.9] - Unreleased

Added

  • 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.

Changed

  • 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.

Fixed

  • Update lags of ForecasterAutoregMultiOutput after grid_search_forecaster().

[0.1.8.1] - 2021-05-17

Added

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

Changed

  • backtesting_forecaster_intervals and backtesting_forecaster print number of steps per fold.

  • Only stored up to 1000 residuals.

  • Improved verbose in backtesting_forecaster_intervals.

Fixed

  • 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.

[0.1.8] - 2021-04-02

Added

  • 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.

Changed

Fixed

[0.1.7] - 2021-03-19

Added

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

Changed

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

Fixed

[0.1.6] - 2021-03-14

Added

  • Method get_feature_importances() to skforecast.ForecasterAutoreg.
  • Added backtesting strategy in grid_search_forecaster().
  • Added backtesting_forecast() to skforecast.model_selection.

Changed

  • 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().

Fixed

[0.1.4] - 2021-02-15

Added

  • Method get_coef() to skforecast.ForecasterAutoreg.

Changed

Fixed