模式识别与人工智能
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  2012, Vol. 25 Issue (6): 922-927    DOI:
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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.
Key wordsConcept Lattice      Intent Waned-Value      Attribute Reduction      Equivalence Relation     
Received: 25 November 2011     
ZTFLH: TP181  
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YANG Kai
MA Yuan
Cite this article:   
YANG Kai,MA Yuan. Multi-Level Attribute Reduction Methods Based on Concept Lattice[J]. , 2012, 25(6): 922-927.
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http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2012/V25/I6/922
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