Feature selection with the boruta package

This article describes a r package boruta,implementing a novel feature selection algorithm for finding 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.