SHAPBoost 1.0.3
Bug Fixes
- Fixed a bug where R² metric was not being correctly maximized in
SHAPBoostRegressor.
SHAPBoost 1.0.2
New Features
- Added
fixed_variables parameter to SHAPBoostRegressor
and SHAPBoostSurvival to allow users to specify variables that should
always be included in the selected feature set.
SHAPBoost 1.0.1
Bug Fixes
- Fixed a bug that caused unsupported types in xgboost for
SHAPBoostRegressor
- Updated compatibility with latest xgboost versions
SHAPBoost 1.0.0
New Features
- Initial release of SHAPBoost package
- Implementation of SHAPBoost algorithm for feature selection using
SHAP values
- Support for regression analysis with
SHAPBoostRegressor
class
- Support for survival analysis with
SHAPBoostSurvival
class
- Integration with XGBoost for gradient boosting
- Support for Cox proportional hazards models in survival
analysis
- Cross-validation based feature selection
- Collinearity detection and handling
- Configurable metrics (MAE, MSE, R², C-index)
Dependencies
- Depends on R >= 3.5.0
- Imports: xgboost, SHAPforxgboost, methods, caret, Matrix
Documentation
- Complete documentation for all exported functions and classes
- Examples for both regression and survival analysis use cases