eXtreme RuleFit R package xrf version 0.3.1 An implementation of the RuleFit algorithm as described in Friedman & Popescu (2008) <doi:10.1214/07-AOAS148>. eXtreme Gradient Boosting ('XGBoost') is used to build rules, and 'glmnet' is used to fit a sparse linear model on the raw and rule features. The result is a model that learns similarly to a tree ensemble, while often offering improved interpretability and achieving improved scoring runtime in live applications. Several algorithms for reducing rule complexity are provided, most notably hyperrectangle de-overlapping. All algorithms scale to several million rows and support sparse representations to handle tens of thousands of dimensions. Software Depends: R (>= 4.3.0) Imports: cli, dplyr, glmnet (>= 3.0), Matrix, methods, rlang, xgboost (>= 3.1.2.1) Suggests: covr, testthat (>= 3.0.0) Karl Holub <karljholub@gmail.com> Comprehensive R Archive Network (CRAN) Karl Holub [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=xrf/LICENSE) 2025-12-17 application/tgz https://CRAN.R-project.org/package=xrf doi:10.32614/CRAN.package.xrf