Added
- Added `Forecaster.transfer_predict()` method. Only univariate sklearn models supported for now (77).
- Added `Forecaster.transfer_cis()` method.
- Added `carry_fit_models` attribute in `Forecaster` object that can be changed when object is initialized.
- Added `util.infer_apply_Xvar_selection()` function.
Changed
- Changed how many history attributes are stored for each evaluated model, making the `Forecaster` object more memory efficient.
- Refactored forecasting code for sklearn models so that model evaluation is more efficient.
- Changed the `max_ar = 'auto'` behavior in `Forecaster.auto_Xvar_select()`.
- Changed scikit-learn dependency to `<1.3.0` due to it not working with the shap library.
Fixed
- Fixed an issue with combo modeling where defaults were not working when a previous model had been run test only.