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niarules: Numerical Association Rule Mining using Population-Based Nature-Inspired Algorithms (original) (raw)

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 ORCID iD [aut, cre, cph], Gerlinde EmsenhuberORCID iD [aut], Jan Hendrik PlümerORCID iD [aut]
Maintainer: Iztok Jr. Fister
BugReports: https://github.com/firefly-cpp/niarules/issues
License: MIT + file
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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