Variable Selection using Random Forests R package varSelRF version 0.7-9 CRAN Task View: ChemPhys (https://CRAN.R-project.org/view=ChemPhys) CRAN Task View: HighPerformanceComputing (https://CRAN.R-project.org/view=HighPerformanceComputing) CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning) Variable selection from random forests using both backwards variable elimination (for the selection of small sets of non-redundant variables) and selection based on the importance spectrum (somewhat similar to scree plots; for the selection of large, potentially highly-correlated variables). Main applications in high-dimensional data (e.g., microarray data, and other genomics and proteomics applications). Software Depends: R (>= 2.0.0), randomForest, parallel Ramon Diaz-Uriarte <rdiaz02@gmail.com> Comprehensive R Archive Network (CRAN) Ramon Diaz-Uriarte [aut, cre] GPL (>= 2) 2026-01-30 application/tgz https://CRAN.R-project.org/package=varSelRF doi:10.32614/CRAN.package.varSelRF