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RecAssoRules: Recursive Mining for Frequent Pattern and Confident Association Rules

Provides functions allowing the user to recursively extract frequent patterns and confident rules according to indicators of minimal support and minimal confidence. These functions are described in "Recursive Association Rule Mining" Abdelkader Mokkadem, Mariane Pelletier, Louis Raimbault (2020) <doi:10.48550/arXiv.2011.14195>.

Version: 1.0
Imports: Rcpp (≥ 1.0.5)
LinkingTo: Rcpp
Published: 2020-12-04
DOI: 10.32614/CRAN.package.RecAssoRules
Author: Louis Raimbault [aut,cre], A.Mokkadem [aut], M.Pelletier [aut]
Maintainer: Louis Raimbault <Louis.Raimbault at icloud.com>
BugReports: https://github.com/LouisRaimbault/RecAssoRules-R
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/LouisRaimbault/RecAssoRules-R
NeedsCompilation: yes
CRAN checks: RecAssoRules results

Documentation:

Reference manual: RecAssoRules.pdf

Downloads:

Package source: RecAssoRules_1.0.tar.gz
Windows binaries: r-devel: RecAssoRules_1.0.zip, r-release: RecAssoRules_1.0.zip, r-oldrel: RecAssoRules_1.0.zip
macOS binaries: r-release (arm64): RecAssoRules_1.0.tgz, r-oldrel (arm64): RecAssoRules_1.0.tgz, r-release (x86_64): RecAssoRules_1.0.tgz, r-oldrel (x86_64): RecAssoRules_1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.