20.500.12556/DKUM-97012 niarules: advancing interpretable machine learning through numerical association rule mining and 3D coral plot visualization Numerical association rule mining remains comparatively underexplored in interpretable machine learning, largely due to the challenges of handling continuous variables and the limited availability of effective visualization techniques. We introduce niarules, an open-source R package that provides a complete and extensible pipeline for numerical association rule mining, complemented by advanced post-processing and interactive 3D visualization. The package integrates bio-inspired optimization-based rule mining methods within a modular architecture that encompasses data preprocessing, rule mining, and visualization. A novel radial layout engine, implemented in C++, generates Coral Plots, which depict rules sharing a common consequent as radial trees. This design facilitates intuitive exploration of antecedent specificity, alongside key quality measures such as support, confidence, and lift. By combining methodological innovation with user-friendly visualization, niarules lowers the entry barrier to numerical association rule mining and supports the development of explainable AI systems for numerical datasets. association rule mining interpretable machine learning numerical association rule mining coral plot visualization asociacijsko pravilo rudarjenje interpretirano strojno učenje rudarjenje pravil numeričnih asociacij vizualizacija koralne ploskve true false false Elsevier B.V. Angleški jezik Slovenski jezik https://www.sciencedirect.com/journal/softwarex © 2025 The Author(s). Članek v reviji 2026-02-11 14:37:26 2026-02-11 14:37:26 2026-07-01 07:24:10 0000-00-00 00:00:00 2026 0 0 7 str. Vol. 33, [article no.] 102470 Feb. 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 2026-02-01 004.8 267744259 10.1016/j.softx.2025.102470 2352-7110 1-s2.0-S2352711025004364-main.pdf 1-s2.0-S2352711025004364-main.pdf 1 6D070C62FBA0CDED220DEAA3974BD9D8 166bd804bc7e03614b9cc826baede078ebecd5aa1f80ad14ea803f046655ebe4 33c38b00-074f-11f1-b759-00155d00019a https://dk.um.si/Dokument.php?lang=slv&id=203222 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0