Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Miron B. Kursa, Witold R. Rudnicki
Title: Feature Selection with the Boruta Package
Abstract: 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.

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Paper: Feature Selection with the Boruta Package     Download PDF (Downloads: 53973)
Supplements:
Boruta_1.3.tar.gz: R source package Download (Downloads: 1110; 19KB)
v36i11.R: R example code from the paper Download (Downloads: 1349; 6KB)
DOI: 10.18637/jss.v036.i11

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.