Abstract
nuggets is a framework for subgroup discovery, contrast and emerging patterns, association rules, and more. Developed as a package for the R statistical environment, nuggets provides a novel and extensible toolkit for performing rule-based analyses. Both crisp (Boolean) and fuzzy data are supported. The package generates conditions in the form of elementary conjunctions, evaluates them on a dataset, and checks the induced sub-data for interesting statistical properties. A user defined function may be evaluated on generated sub-dataset, which provides a novel generality. The aim of this paper is to present that free software to the soft computing community, as the tool could be useful to both researchers and analysts in the domain of pattern mining, as, besides searching for various existing pattern types, brand new ideas may be easily implemented and evaluated within that framework.
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Notes
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CRAN is the Comprehensive R Archive Network, a network of servers providing identical and up-to-date versions of R and R packages.
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Acknowledgment
The study described is from the project “Research of Excellence on Digital Technologies and Wellbeing CZ.02.01.01/00/22_008/0004583” which is co-financed by the European Union.
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Burda, M. (2024). nuggets: Data Pattern Extraction Framework in R. In: Torra, V., Narukawa, Y., Kikuchi, H. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2024. Lecture Notes in Computer Science(), vol 14986. Springer, Cham. https://doi.org/10.1007/978-3-031-68208-7_10
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