Package: niarules 0.2.0

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>.

Authors:Iztok Jr. Fister [aut, cre, cph]

niarules_0.2.0.tar.gz
niarules_0.2.0.zip(r-4.5)niarules_0.2.0.zip(r-4.4)niarules_0.2.0.zip(r-4.3)
niarules_0.2.0.tgz(r-4.5-any)niarules_0.2.0.tgz(r-4.4-any)niarules_0.2.0.tgz(r-4.3-any)
niarules_0.2.0.tar.gz(r-4.5-noble)niarules_0.2.0.tar.gz(r-4.4-noble)
niarules_0.2.0.tgz(r-4.4-emscripten)niarules_0.2.0.tgz(r-4.3-emscripten)
niarules.pdf |niarules.html
niarules/json (API)

# Install 'niarules' in R:
install.packages('niarules', repos = c('https://firefly-cpp.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/firefly-cpp/niarules/issues

On CRAN:

Conda:

association-rulesmetaheuristicsoptimization

3.70 score 1 stars 2 scripts 255 downloads 21 exports 0 dependencies

Last updated 23 days agofrom:f370c15ac5. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 04 2025
R-4.5-winNOTEMar 04 2025
R-4.5-macNOTEMar 04 2025
R-4.5-linuxNOTEMar 04 2025
R-4.4-winNOTEMar 04 2025
R-4.4-macNOTEMar 04 2025
R-4.4-linuxNOTEMar 04 2025
R-4.3-winNOTEMar 04 2025
R-4.3-macNOTEMar 04 2025

Exports:add_attributebuild_rulecalculate_bordercalculate_fitnesscalculate_selected_categorycheck_attributecut_pointdifferential_evolutionevaluateextract_feature_infofeature_positionfix_bordersmap_to_tsparticle_swarm_optimizationprint_association_rulesprint_feature_infoproblem_dimensionread_datasetrssupp_confwrite_association_rules_to_csv

Dependencies: