JACIII Vol.15 No.1 pp. 102-109
doi: 10.20965/jaciii.2011.p0102


Heuristic Algorithm for Attribute Reduction Based on Classification Ability by Condition Attributes

Yasuo Kudo* and Tetsuya Murai**

*Graduate School of Engineering, Muroran Institute of Technology, 27-1 Mizumoto, Muroran 050-8585, Japan

**Graduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-Ku, Sapporo 060-0814, Japan

February 27, 2010
April 22, 2010
January 20, 2011
rough set, attribute reduction, heuristic algorithm, classification ability
The heuristic algorithm we propose to compute a relative reduct candidate is based on evaluating classification ability of condition attributes. Considering the discernibility and equivalence of objects for condition attributes in relative reducts, we introduce evaluation criteria for condition attributes and relative reducts. The computational complexity of the proposed algorithm is O(|U|2|C|2). Experimental results indicate that our algorithm often generates a relative reduct producing a good evaluation result.
Cite this article as:
Y. Kudo and T. Murai, “Heuristic Algorithm for Attribute Reduction Based on Classification Ability by Condition Attributes,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.1, pp. 102-109, 2011.
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