v1.2.3

• add conditional quantile as threshold for the sdp in regression by default
• monte carlo search to find the maximal rules
• v1 implementation of counterfactual rules
• fixed bugs for python 3.10 support

v1.2.2

• Automated wheel building with github workflows

v1.2.1

• Fixed compatibility issue with numba, shap, shapash

v1.2.0

• Add a glass-box model, namely global rule-based models based on Sufficient Rules.
• Show the efficiency of the global rule-based models w.r.t SOTA on toy dataset, see the notebook.
• Add Shapley Values of the agnostic Explainer in the WebApp with Leaf estimator.
• Stable version of Coalitional version of Shapley Values based on Leaf estimator, and SDP-Sufficient Explanations-Sufficient Rules of the Agnostic explainer.