varSelRF0.7-8 package

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).

  • Maintainer: Ramon Diaz-Uriarte
  • License: GPL (>= 2)
  • Last published: 2017-07-10