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) <>. 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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: gmp (>= 4.2.0), gsl
CRAN checks: sbrl results


Reference manual: sbrl.pdf


Package source: sbrl_1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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