International Journal of Education and Management Engineering(IJEME)

ISSN: 2305-3623 (Print), ISSN: 2305-8463 (Online)

Published By: MECS Press

IJEME Vol.1, No.1, Jul. 2011

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

Full Text (PDF, 1006KB), PP.6-11

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Guijuan Song

Index Terms

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


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.


[1]Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences 11 (1982) 341-356.

[2]PawlakZ.Rough set approach to multi-attribute decision analysis [J].European Journal of Operational Research,1994,72:443-459.

[3]Wenxiu Zhang,Weizhi Wu,Jiye Liang.Theory and Approach in Rough Set[M].Beijing:Science Press,2001(in Chinese). 

[4]D.Q. Miao, J. Wang, An information representation of the concepts and operations in rough set theory, Journal of Software 10 (1999) 113-116 (in Chinese).

[5]D.Q. Miao,Daoguo Li.Theory,algorithm and application in rough set[M]. beijing:tsinghua university press.2008,4(in Chinese).

[6]Skowron, A, Rauszer, C., “The discernibility matrices and functions in information systems”, Slowifiski(Ed.), Intelligent decision support: Handbook of applications and advances of rough set theory, Kluwer Academic Publishers, Dordrecht, volume 11, 1992, pp.331-362.