Probatus

Improvements in this release:
- Create a comparison of imputation strategies 86
- Added support for passing check_additivity argument 103
- Range of code styling issues fixed, based on precommit config 100
- Renamed TreeDependencePlotter to DependencePlotter and exposed the docs 94
- Enable instalation of extra dependencies 97
- Added how to notebook to ensure reproducibility 99
- Description of vision of probatus 91

Improvements in this release:
- Bugfix, allow passing kwargs to dependence plot in ShapModelInterpreter 90

Improvements in this release:
- ShapRFECV supports all sklearn compatible search CVs. 76 49

Improvements in this release:
- Added features list to README 53
- Added docs for sample row functionality 54
- Added 'open in colab' badges to tutorial notebooks 56
- Deploy documentation on release 47
- Added columns_to_keep for shap feature elimination 63
- Updated docs for usage of columns to keep functionality in SHAPRFECV 66
- Added shap support for linear models 69
- Installed probatus in colab notebooks 80
- Minor infrastructure tweaks 81

Various improvements to the consistency and usability of the package
- Unit test docstring and notebooks 41
- Unified scoring metric within probatus 27
- Improve docstrings consistency documentation 25
- Implemented unified interface 24
- Added images to API docs documentation 23
- Added verbose parameter to ShapRFECV 21
- Make API more consistent 19
- Set model parameter name to clf across probatus
- Set default random_state to None
- Ensure that verbose is used consistently in probatus
- Unify parameter class_names for classes in which it is relevant
- Add return scores parameter to compute wherever applicable
- Add sample row functionality to utils 17
- Make an experiment comparing sklearn.RFECV with ShapRFECV 16
- ShapModelInterpreter calculate train set feature importance 13

Improved
- Docs and API of ShapRFECV 11