CRAN/E | xrf

xrf

eXtreme RuleFit

Installation

About

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.

github.com/holub008/xrf
Bug report File report

Key Metrics

Version 0.2.2
R ≥ 3.1.0
Published 2022-10-04 570 days ago
Needs compilation? no
License MIT
License File
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Maintainer

Maintainer

Karl Holub

karljholub@gmail.com

Authors

Karl Holub

aut / cre

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

xrf archive

Depends

R ≥ 3.1.0

Imports

Matrix
glmnet ≥ 3.0
xgboost ≥ 0.71.2
dplyr
fuzzyjoin
rlang
methods

Suggests

testthat
covr

Reverse Suggests

rules