CC BY 4.0Burda, Michal2026-02-062026-02-062026BURDA, Michal, 2026. Discovering Fuzzy and Statistical Patterns in Data: The Nuggets R Package. Online. In: ; STUPŇANOVÁ, Andrea and PAVLISKA, Viktor (eds.). Proceedings of The Eighteenth International Conference on Fuzzy Set Theory and Applications. Ostrava: University of Ostrava, p. 29-32. ISBN 978-80-7599-515-5. Available at: https://doi.org/10.15452/978-80-7599-515-5.2026.03.10.15452/978-80-7599-515-5.2026.03https://eduo.osu.cz/handle/1/226The nuggets package provides a flexible and extensible framework for discovering interpretable data patterns based on frequent logical conditions. Its design unifies classical association – rule mining with linguistic and fuzzy representations, while enabling optional statistical evaluation for selected pattern types such as conditional contrasts and correlations. Pattern generation is driven by support, ensuring efficient mining of relevant conditions, whereas additional quantitative analyses or tests can be seamlessly attached when desired. A major strength of nuggets lies in its extensibility. The framework allows users to define custom fuzzification schemes and to evaluate an arbitrary R function on every frequent condition, thereby enabling the creation of new, user-defined pattern types. This design encourages experimentation with alternative logical semantics, statistical measures, and application – specific evaluation criteria, making nuggets not only a tool for applied pattern discovery but also a research platform for developing new methods.enfuzzy systemsmathematicsinformaticsassociation rulesR packagefuzzy rulesinfo:eu-repo/semantics/conferencePaper519.1/.8 - Kombinatorika. Teorie grafů. Matematická statistika. Operační výzkum. Matematické modelovánífuzzy systémymatematikainformatika