Package: VSURF
Type: Package
Title: Variable Selection Using Random Forests
Version: 0.5
Date: 2013-05-28
Author: Robin Genuer, Jean-Michel Poggi and Christine Tuleau-Malot
Maintainer: Robin Genuer <Robin.Genuer@isped.u-bordeaux2.fr>
Description: Three steps variable selection procedure based on random
        forests. Initially developed to handle high dimensional data
        (for which number of variables largely exceeds number of
        observations), the package is very versatile and can treat most
        dimensions of data, for regression and supervised
        classification problems.  First step is dedicated to eliminate
        irrelevant variables from the dataset.  Second step aims to
        select all variables related to the response for interpretation
        purpose.  Third step refines the selection by eliminating
        redundancy in the set of variables selected by the second step,
        for prediction purpose.
License: GPL (>= 2)
Depends: randomForest, rpart
Packaged: 2013-05-28 14:47:12 UTC; robin
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-05-28 17:36:16
