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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