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Searching minimal attribute reduction sets based on combination of the binary discernibility matrix and graph theory

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3 Author(s)
Fei Hao ; Sch. of Math. & Comput. Eng., Xihua Univ., Chengdu ; Zheng Pei ; Shengtong Zhong

Attribute reduction plays an important role in rough set theory. It is an important application in data mining. In this paper, we focus on discussing the relation between set covering and attribute reduction in rough set theory. Based on the equivalence between minimal set covering and minimal attribute reduction sets, attribute reduction graph (ARG) is constructed. A novel algorithm to find the minimal attribute reduction sets, which is based on combination of binary discernibility matrix and graph theory is proposed in this paper. This algorithm demonstrates its efficiency and feasibility by an example.

Published in:

Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on

Date of Conference:

1-6 June 2008

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