Package: xrf 0.2.2

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.

Authors:Karl Holub [aut, cre]

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Bug tracker:https://github.com/holub008/xrf/issues

On CRAN:

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Last updated 2 years agofrom:65aa6bd4c7. Checks:OK: 7. Indexed: yes.

Exports:xrf

Dependencies:clicodetoolscpp11data.tabledplyrfansiforeachfuzzyjoingenericsgeosphereglmnetglueiteratorsjsonlitelatticelifecyclemagrittrMatrixpillarpkgconfigpurrrR6RcppRcppEigenrlangshapespstringdiststringistringrsurvivaltibbletidyrtidyselectutf8vctrswithrxgboost