niarules: Numerical Association Rule Mining using Population-Based
Nature-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 + file LICENSE | 
| URL: | https://github.com/firefly-cpp/niarules | 
| NeedsCompilation: | yes | 
| Classification/ACM: | G.4, H.2.8 | 
| Materials: | README, NEWS | 
| CRAN checks: | niarules results | 
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=niarules
to link to this page.