%0 Journal Article
%T Feature Selection with the Boruta Package
%A Miron B. Kursa
%A Witold R. Rudnicki
%J Journal of Statistical Software
%D 2010
%I University of California, Los Angeles
%X This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.
%K feature selection
%K feature ranking
%K random forest
%U http://www.jstatsoft.org/v36/i11/paper