Package: sbrl
Type: Package
Title: Scalable Bayesian Rule Lists Model
Version: 1.4
Date: 2024-04-07
Authors@R: c(person("Hongyu", "Yang", role = c("aut", "cre"),
		     email = "edwardyhy1@gmail.com"),
	      person("Morris", "Chen", role = "ctb",
		     email = "Morris_CM_Chen@wistron.com"),
	      person("Cynthia", "Rudin", role = c("aut", "ctb"),
		     email = "rudin@cs.duke.edu"),
	      person("Margo", "Seltzer", role = c("aut", "ctb"),
		     email = "mseltzer@cs.ubc.ca"),
	      person("The President and Fellows of Harvard College",
                     role = c("cph")))
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@gmail.com>
Description: 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.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.4), arules, methods
RcppModules: sbrl
LinkingTo: Rcpp
NeedsCompilation: yes
LazyData: yes
SystemRequirements: gmp (>= 4.2.0), gsl
Packaged: 2026-07-13 06:10:31 UTC; root
Config/pak/sysreqs: libgmp3-dev libgsl0-dev
Repository: https://hongyuy.r-universe.dev
Date/Publication: 2024-04-09 02:33:00 UTC
RemoteUrl: https://github.com/cran/sbrl
RemoteRef: HEAD
RemoteSha: 76a0e9f5ee7576667ed2813ed648d7bc413df729