Reverted to updating the intercept in each boosting step. The reason is slightly better predictiveness on several datasets.
6.0.0
- Deprecated the constructor field intercept in APLRRegressor. - Bugfix related to the Python wrapper that previously did not pickle correctly. - Bugfix related to a warning when the model has not been trained yet but is attempted used.
5.0.0
Changed intercept estimation methodology and consequently deprecated intercept_steps. The intercept is now fully estimated in the first boosting step.
4.1.0
Improved fitting when group_mse is used as a loss function. Fixed a minor bug related to handling of incorrect user input (an error is now thrown if m=0).
4.0.0
Added APLRClassifier, enabling two-class and multi-class classification. Also two small bugfixes in APLRRegressor and a renaming of the get_m() method to get_optimal_m().