Package: arc 1.4.2

arc: Association Rule Classification

Implements the Classification-based on Association Rules (CBA) algorithm for association rule classification. The package, also described in Hahsler et al. (2019) <doi:10.32614/RJ-2019-048>, contains several convenience methods that allow to automatically set CBA parameters (minimum confidence, minimum support) and it also natively handles numeric attributes by integrating a pre-discretization step. The rule generation phase is handled by the 'arules' package. To further decrease the size of the CBA models produced by the 'arc' package, postprocessing by the 'qCBA' package is suggested.

Authors:Tomas Kliegr [aut, cre]

arc_1.4.2.tar.gz
arc_1.4.2.zip(r-4.7)arc_1.4.2.zip(r-4.6)arc_1.4.2.zip(r-4.5)
arc_1.4.2.tgz(r-4.6-any)arc_1.4.2.tgz(r-4.5-any)
arc_1.4.2.tar.gz(r-4.7-any)arc_1.4.2.tar.gz(r-4.6-any)
arc_1.4.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
arc/json (API)

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

Bug tracker:https://github.com/kliegr/arc/issues

Datasets:
  • humtemp - Comfort level based on temperature and humidity of the environment

On CRAN:

Conda:

5.16 score 7 stars 1 packages 46 scripts 391 downloads 3 mentions 16 exports 8 dependencies

Last updated from:02b904742d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK164
linux-release-x86_64OK138
macos-release-arm64OK109
macos-oldrel-arm64OK94
windows-develOK96
windows-releaseOK82
windows-oldrelOK98
wasm-releaseOK135

Exports:applyCutapplyCutscbacba_manualcbaCSVcbaIriscbaIrisNumericCBARuleModelCBARuleModelAccuracydiscretizeUnsuperviseddiscrNumericgetAppearancegetConfVectorForROCmdlp2prunetopRules

Dependencies:arulesdiscretizationgenericslatticeMatrixR.methodsS3R.ooR.utils