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.
- Version0.2.2
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release10/04/2022
Documentation
Team
Karl Holub
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