xrf: eXtreme RuleFit

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.

Getting started

Package details

AuthorKarl Holub [aut, cre]
MaintainerKarl Holub <[email protected]>
LicenseMIT + file LICENSE
URL https://github.com/holub008/xrf
Package repositoryView on CRAN
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xrf documentation built on May 2, 2019, 5:57 a.m.