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:
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