Rules offer an invaluable combination of predictive and descriptive capabilities. Our package for rule-based data analysis, RuleKit, has proven its effectiveness in classification, regression, and survival problems. Here we present its second version. New algorithms and optimized implementations of those previously included, significantly improved the computational performance of our suite, reducing the analysis time of some data sets by two orders of magnitude. The usability of RuleKit 2 is provided by two new components: Python package and browser application with a graphical user interface. The former complies with scikit-learn, the most popular data mining library for Python, allowing RuleKit 2 to be straightforwardly integrated into existing data analysis pipelines. RuleKit 2 is available at GitHub under GNU AGPL 3 license (this https URL)
View on arXiv@article{gudyś2025_2504.20650,
title={ RuleKit 2: Faster and simpler rule learning },
author={ Adam Gudyś and Cezary Maszczyk and Joanna Badura and Adam Grzelak and Marek Sikora and Łukasz Wróbel },
journal={arXiv preprint arXiv:2504.20650},
year={ 2025 }
}