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-any)arc_1.4.2.zip(r-4.6-any)arc_1.4.2.zip(r-4.5-any)
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:

5.15 score 7 stars 1 packages 45 scripts 589 downloads 3 mentions 16 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK126
source / vignettesOK141
linux-releaseOK123
macos-releaseOK96
macos-oldrelOK115
windows-develOK82
windows-releaseOK92
windows-oldrelOK90
wasm-releaseOK101

Exports:applyCutapplyCutscbacba_manualcbaCSVcbaIriscbaIrisNumericCBARuleModelCBARuleModelAccuracydiscretizeUnsuperviseddiscrNumericgetAppearancegetConfVectorForROCmdlp2prunetopRules

Dependencies:arulesdiscretizationgenericslatticeMatrixR.methodsS3R.ooR.utils