varSelRF: Variable Selection using Random Forests

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).

AuthorRamon Diaz-Uriarte <>
Date of publication2014-12-14 12:13:58
MaintainerRamon Diaz-Uriarte <>
LicenseGPL (>= 2)

View on CRAN

Questions? Problems? Suggestions? or email at

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.