Added functionality from SHAP so that `wideboost` models can be interpreted easily.
0.2.0
Added `wlgb`, the wideboost wrapper on LightGBM. Added examples using `wlgb`.
0.1.3
Removed sklearn functions from wxgb file to remove it as a dependency to run the core wxgb functions.
0.1.2
Original release with bugfixes:
BUGFIX - install issues
0.1.1
Original release with some basic bugfixes.
BUGFIX: - fixed some install issues.
0.1
First release of `wideboost`. Implements basic Wide Boosting for binary classification, multi-class classification and regression. Currently only uses XGBoost as its backend.