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:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=sbrl
to link to this page.