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.
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