Research on Feature Selection Algorithm in Rough Set Based on Information Entropy

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Author(s)

Guijuan Song 1,*

1. Dalian Neusoft Institute of Information Dalian, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijeme.2011.01.02

Received: 6 Apr. 2011 / Revised: 18 May 2011 / Accepted: 23 Jun. 2011 / Published: 29 Jul. 2011

Index Terms

Rough set, attribute reduction, decision table, discernibility matrix, information entropy

Abstract

Rough set theory is an effective approach to imprecision, vagueness, and incompleteness in classification analysis and knowledge discovery .Attribute reduction is a key problem for rough set theory. While computing reduction according to the definitions is a typical NP problem. In this paper, basic concept of rough set theory is presented, one heuristic algorithm for attribution reduction based on conditional entropy is proposed. The actual application shows that the method is feasible and effective.

Cite This Paper

Guijuan Song,"Research on Feature Selection Algorithm in Rough Set Based on Information Entropy", IJEME, vol.1, no.1, pp.6-11, 2011. DOI: 10.5815/ijeme.2011.01.02

Reference

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