Add new classifiers, SlipperRuleClassifier, BOAClassifier, CorelsRuleListClassifier. Cleaned up some discretizer code. Updated docs
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Working support for py3.6 and added new models including BoostedRuleSet and OneRRuleLis
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
This release cleans up dependencies as well as started a more unified API for rule sets
add function to explain classification errors improve string printing for several models, especially...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Sklearn-compatible package of interpretable ML models (imodels package) for concise and accurate pre...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Working support for py3.6 and added new models including BoostedRuleSet and OneRRuleLis
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
This release cleans up dependencies as well as started a more unified API for rule sets
add function to explain classification errors improve string printing for several models, especially...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Sklearn-compatible package of interpretable ML models (imodels package) for concise and accurate pre...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
Working support for py3.6 and added new models including BoostedRuleSet and OneRRuleLis
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compat...
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