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.
- Version1.4
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release04/08/2024
Team
Hongyu Yang
Cynthia Rudin
Show author detailsRolesAuthor, ContributorMargo Seltzer
Show author detailsRolesAuthor, ContributorMorris Chen
Show author detailsRolesContributorThe President and Fellows of Harvard College
Show author detailsRolesCopyright holder
Insights
Last 30 days
This package has been downloaded 187 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,421 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Apr 14, 2024 with 36 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Linking To1 package
- Reverse Suggests1 package