varSelRF v0.7-8


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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).



An R package for variable selection using random Forest.


Diaz-Uriarte and Alvarez de Andres, 2006, "Gene selection and classification of microarray data using random forest.", BMC Bioinformatics, 2006, 7:3 (with Supplementary Material)

Diaz-Uriarte, 2007, "GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest." BMC Bioinformatics, 8: 328.


GPL (>= 2)

Functions in varSelRF

Name Description
plot.varSelRF Plot a varSelRF object
plot.varSelRFBoot plot a varSelRFBoot object
randomVarImpsRF Variable importances from random forest on permuted class labels
randomVarImpsRFplot Plot random random variable importances
varSelRFBoot Bootstrap the variable selection procedure in varSelRF
varSelImpSpecRF Variable selection using the "importance spectrum"
varSelRF Variable selection from random forests using OOB error
selProbPlot Selection probability plot for variable importance from random forests
summary.varSelRFBoot Summary of a varSelRFBoot object
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Last month downloads


Date 2017-07-10
LazyLoad Yes
License GPL (>= 2)
Repository CRAN
Date/Publication 2017-07-10 13:54:22 UTC
Packaged 2017-07-10 10:47:03.738 UTC; ramon
NeedsCompilation no

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