Aplr

**Changes:**
- Added the constructor parameter _early_stopping_rounds_ with a default value of 500, meaning that if the validation loss does not improve during 500 boosting steps then boosting is aborted to save time. Due to _early_stopping_rounds_ it may make sense to try higher values of _m_ (max number of boosting steps).
- Updated documentation.
- Changed default values of _m_ for _APLRRegressor_ and _APLRClassifier_ and _v_ (learning rate) for _APLRClassifier_.

Fixed a bug where sample weights could be incorrectly used when estimating the split point for a term.

Fixed a bug that capped predictions too much when the cap_predictions_to_minmax_in_training argument in the predict method is True.

Fixed a rare and minor bug related to split point estimation.

Bugfix related to multi-threading library not loading in some environments.

- Improved the implementation of multi-threading.
- Simplified term names.
- Printing more information about training progress.