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Feature Selection with the Boruta Package

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  • Kursa, Miron B.
  • Rudnicki, Witold R.

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.

Suggested Citation

  • Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
    • Handle: RePEc:jss:jstsof:v:036:i11
    DOI: http://hdl.handle.net/10.18637/jss.v036.i11
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