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sbrl: Scalable Bayesian Rule Lists Model

An efficient implementation of Scalable Bayesian Rule Lists Algorithm, a competitor algorithm for decision tree algorithms; see Hongyu Yang, Cynthia Rudin, Margo Seltzer (2017) <https://proceedings.mlr.press/v70/yang17h.html>. It builds from pre-mined association rules and have a logical structure identical to a decision list or one-sided decision tree. Fully optimized over rule lists, this algorithm strikes practical balance between accuracy, interpretability, and computational speed.

Version:1.4
Imports:Rcpp (≥ 0.12.4),arules, methods
LinkingTo:Rcpp
Published:2024-04-08
DOI:10.32614/CRAN.package.sbrl
Author:Hongyu Yang [aut, cre], Morris Chen [ctb], Cynthia Rudin [aut, ctb], Margo Seltzer [aut, ctb], The President and Fellows of Harvard College [cph]
Maintainer:Hongyu Yang <edwardyhy1 at gmail.com>
License:GPL-2 |GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:yes
SystemRequirements:gmp (>= 4.2.0), gsl
CRAN checks:sbrl results

Documentation:

Reference manual:sbrl.html ,sbrl.pdf

Downloads:

Package source: sbrl_1.4.tar.gz
Windows binaries: r-devel:sbrl_1.4.zip, r-release:sbrl_1.4.zip, r-oldrel:sbrl_1.4.zip
macOS binaries: r-release (arm64):sbrl_1.4.tgz, r-oldrel (arm64):sbrl_1.4.tgz, r-release (x86_64):sbrl_1.4.tgz, r-oldrel (x86_64):sbrl_1.4.tgz
Old sources: sbrl archive

Reverse dependencies:

Reverse suggests:qCBA

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=sbrlto link to this page.


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