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arc
View on CRAN: Click
here
Download and install arc package within the R console
Install from CRAN:
install.packages("arc")
Install from Github:
library("remotes")
install_github("cran/arc")
Install by package version:
library("remotes")
install_version("arc", "1.4")
Attach the package and use:
library("arc")
Maintained by
Tomas Kliegr
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-09-07
Latest Update: 2023-08-17
Description:
Implements the Classification-based on
Association Rules (CBA) algorithm for association rule classification.
The package, also described in Hahsler et al. (2019) ,
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.
How to cite:
Tomas Kliegr (2016). arc: Association Rule Classification. R package version 1.4, https://cran.r-project.org/web/packages/arc. Accessed 06 Nov. 2024.
Previous versions and publish date:
Other packages that cited arc R package
View arc citation profile
Other R packages that arc depends,
imports, suggests or enhances
Complete documentation for arc
Functions, R codes and Examples using
the arc R package
Some associated functions: CBARuleModel-class . CBARuleModelAccuracy . applyCut . applyCuts . cba . cbaCSV . cbaIris . cbaIrisNumeric . cba_manual . discrNumeric . discretizeUnsupervised . getAppearance . getConfVectorForROC . humtemp . mdlp2 . predict.CBARuleModel . prune . topRules .
Some associated R codes: cba.R . cutSemicolon.R . datasets.R . m1prune.R . mdlp2.R . toprules.R . Full arc package functions and examples
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