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
card.svg |card.png
arc/json (API)
NEWS

# 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:

4.62 score 7 stars 1 packages 40 scripts 306 downloads 16 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK142
source / vignettesOK140
linux-release-x86_64OK128
macos-release-arm64OK82
macos-oldrel-arm64OK103
windows-develOK92
windows-releaseOK93
windows-oldrelOK85
wasm-releaseOK101

Exports:applyCutapplyCutscbacba_manualcbaCSVcbaIriscbaIrisNumericCBARuleModelCBARuleModelAccuracydiscretizeUnsuperviseddiscrNumericgetAppearancegetConfVectorForROCmdlp2prunetopRules

Dependencies:arulesdiscretizationgenericslatticeMatrixR.methodsS3R.ooR.utils