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Multi-Level Attribute Reduction Methods Based on Concept Lattice |
YANG Kai, MA Yuan |
School of Software,University of Science and Technology LiaoNing,Anshan 114051 |
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Abstract Attribute reduction is the kernel contents of rough set theory.Concept lattice is effective for knowledge representation and data analysis. Multi-level attribute reduction algorithm based on concept lattice is proposed by using concept lattice as reduction tool. The concepts including discriminable concepts, equivalent concepts and wane-n level are also introduced. The infuence of intent waned-value producing impact on the change of classification ability and the judge theorems of attribute reduction in concept lattice are mainly studied. The proposed algorithm discovers all the maximal reductions completely and an effective approach is presented to attribute reduction in concept lattice. Finally, a real example and experiment comparisons demonstrate both its feasibility and effectiveness.
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Received: 25 November 2011
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