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: 0.1.0
Depends: R (≥ 4.0.0)
Imports: stats, utils
Suggests: testthat
Published: 2024-03-09
Author: Iztok Jr. Fister ORCID iD [aut, cre, cph]
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: no
Classification/ACM: G.4, H.2.8
Materials: README
CRAN checks: niarules results

Documentation:

Reference manual: niarules.pdf

Downloads:

Package source: niarules_0.1.0.tar.gz
Windows binaries: r-prerel: niarules_0.1.0.zip, r-release: niarules_0.1.0.zip, r-oldrel: niarules_0.1.0.zip
macOS binaries: r-prerel (arm64): niarules_0.1.0.tgz, r-release (arm64): niarules_0.1.0.tgz, r-oldrel (arm64): niarules_0.1.0.tgz, r-prerel (x86_64): niarules_0.1.0.tgz, r-release (x86_64): niarules_0.1.0.tgz

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