Interpret

Fixed
- resolved new scikit-learn requirement for having \_\_sklearn\_tags\_\_
- changed position of ClassifierMixin and RegressorMixin inheritance to satisfy scikit-learn check
- reliable handling of sparse arrays (previously only sparse matrices worked)

Changed
- minimum python version increased to 3.9
- minimum numpy version increased to 1.25
Fixed
- removed scipy dependency to resolve Issue 588

Changed
- added predict_with_uncertainty function by degenfabian in PR 584
- handle mono-classification in SHAP by degenfabian in PR 582
- improvements to tree building in C++
Fixed
- issue that develop/debug options were not being honored in Windows when 1<n_jobs in joblib
- fix several bugs in C++ from negative hessians or negative gain values caused by floating point noise

Changed
- default EBM parameters changed to improve model performance
- switch to using exact versions of exp/log instead of the previously used approximate versions
Fixed
- fix issue where very large feature values fail in the UI PR 581 by degenfabian

Added
- support for regularization parameters reg_alpha, and reg_lambda in EBMs
- support for the parameter max_delta_step in EBMs
- improved fitting speed for most of the alternative objectives

Added
- visualizations for the APRL (Automatic Piecewise Linear Regression) package by mathias-von-ottenbreit
Changed
- early_stopping_tolerance default changed to 1e-5 to reduce EBMs fitting time slightly
- shuffle initial feature order within each bag and during greedy boosting
Fixed
- fixed numpy 2.0 issue in the Marginal class