@article{JSSv036i11,
title={Feature Selection with the Boruta Package},
volume={36},
url={https://www.jstatsoft.org/index.php/jss/article/view/v036i11},
doi={10.18637/jss.v036.i11},
abstract={This article describes a <b>R</b> package <b>Boruta</b>, 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 <b>Boruta</b> package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.},
number={11},
journal={Journal of Statistical Software},
author={Kursa, Miron B. and Rudnicki, Witold R.},
year={2010},
pages={1–13}
}