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).

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

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