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sbrl  

Scalable Bayesian Rule Lists Model
View on CRAN: Click here


Download and install sbrl package within the R console
Install from CRAN:
install.packages("sbrl")

Install from Github:
library("remotes")
install_github("cran/sbrl")

Install by package version:
library("remotes")
install_version("sbrl", "1.4")



Attach the package and use:
library("sbrl")
Maintained by
Hongyu Yang
[Scholar Profile | Author Map]
First Published: 2016-06-15
Latest Update: 2024-03-26
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) . 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.
How to cite:
Hongyu Yang (2016). sbrl: Scalable Bayesian Rule Lists Model. R package version 1.4, https://cran.r-project.org/web/packages/sbrl. Accessed 29 Apr. 2025.
Previous versions and publish date:
1.0 (2016-06-15 08:33), 1.1 (2016-07-24 16:13), 1.2 (2016-07-29 06:41), 1.3 (2024-03-26 17:50)
Other packages that cited sbrl R package
View sbrl citation profile
Other R packages that sbrl depends, imports, suggests or enhances
Complete documentation for sbrl
Functions, R codes and Examples using the sbrl R package
Full sbrl package functions and examples
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