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.