niarules: Numerical Association Rule Mining using Population-BasedNature-Inspired Algorithms
Framework is devoted to mining numerical association rules through the utilization of nature-inspired algorithms for optimization. Drawing inspiration from the 'NiaARM' 'Python' and the 'NiaARM' 'Julia' packages, this repository introduces the capability to perform numerical association rule mining in the R programming language. Fister Jr., Iglesias, Galvez, Del Ser, Osaba and Fister (2018) <doi:10.1007/978-3-030-03493-1_9>.
| Version: | 0.3.1 |
| Depends: | R (≥ 4.0.0) |
| Imports: | stats, utils,Rcpp,dplyr,rlang,rgl |
| LinkingTo: | Rcpp |
| Suggests: | testthat,withr |
| Published: | 2025-09-15 |
| DOI: | 10.32614/CRAN.package.niarules |
| Author: | Iztok Jr. Fister [aut, cre, cph], Gerlinde Emsenhuber [aut], Jan Hendrik Plümer [aut] |
| Maintainer: | Iztok Jr. Fister <iztok at iztok.space> |
| BugReports: | https://github.com/firefly-cpp/niarules/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/firefly-cpp/niarules |
| NeedsCompilation: | yes |
| Classification/ACM: | G.4, H.2.8 |
| Materials: | README,NEWS |
| CRAN checks: | niarules results |
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