Package: xrf 0.3.1
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:
xrf_0.3.1.tar.gz
xrf_0.3.1.zip(r-4.7)xrf_0.3.1.zip(r-4.6)xrf_0.3.1.zip(r-4.5)
xrf_0.3.1.tgz(r-4.6-any)xrf_0.3.1.tgz(r-4.5-any)
xrf_0.3.1.tar.gz(r-4.7-any)xrf_0.3.1.tar.gz(r-4.6-any)
xrf_0.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
xrf/json (API)
| # Install 'xrf' in R: |
| install.packages('xrf', repos = c('https://holub008.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/holub008/xrf/issues
Last updated from:eb2449db22. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 141 | ||
| source / vignettes | OK | 178 | ||
| linux-release-x86_64 | OK | 202 | ||
| macos-release-arm64 | OK | 189 | ||
| macos-oldrel-arm64 | OK | 193 | ||
| windows-devel | OK | 132 | ||
| windows-release | OK | 104 | ||
| windows-oldrel | OK | 96 | ||
| wasm-release | OK | 106 |
Exports:xrf
Dependencies:clicodetoolsdata.tabledplyrforeachgenericsglmnetglueiteratorsjsonlitelatticelifecyclemagrittrMatrixpillarpkgconfigR6RcppRcppEigenrlangshapesurvivaltibbletidyselectutf8vctrswithrxgboost
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Produce rules & coefficients for the RuleFit model | coef.xrf |
| Generate the design matrix from an eXtreme RuleFit model | model.matrix.xrf |
| Draw predictions from a RuleFit xrf model | predict.xrf |
| Print an eXtreme RuleFit model | print.xrf |
| Summarize an eXtreme RuleFit model | summary.xrf |
| Fit an eXtreme RuleFit model | xrf |
| Fit an eXtreme RuleFit model | xrf.formula |
