Pgbm

* Added Python 3.11 testing scripts to wheel
* Update scikit-learn minimum dependency requirement to 1.2
* Update MacOSX minimum dependency to MacOSX 10.13

* Fixed bug in sklearn cython code

* Fixed bug in missing values in scikit-learn wrapper for Torch backend

* Added support for missing values in Torch backend
* Fixed documentation not rendering properly

* Added `HistGradientBoostingRegressor`, a fork of scikit-learn's version that allows to use PGBM whilst being fully compatible with scikit-learn
* Deprecated `pgbm_nb` in favor of `HistGradientBoostingRegressor`.
* Restructured the package; the Torch version (`PGBMRegressor`) is now available under `pgbm.torch`, whereas the scikit-learn version is available under `pgbm.sklearn`, and the distributed version under `pgbm.dist`

* Fixed bug in PGBMRegressor not returning sample_statistics properly
* Train and validation metrics are now an attribute of a fitted learner