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  2008, Vol. 21 Issue (1): 34-41    DOI:
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Cluster Validity Function Based on Fuzzy Degree
CHEN Duo1,2, LI Xue1,3, CUI DuWu1, FEI Rong1
1.School of Computer Science and Engineering, Xi'an University of Technology, Xi'an 7100482.
Computer Centre, Tangshan College, Tangshan 0630003.
International Business School, Shanxi Normal University, Xi'an 710062

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Abstract  Construction of cluster validity function is a commonly used method to determine the optimal partition and optimal number of clusters for fuzzy partitions. Based on the basic theory of fuzzy set, the notion of cluster fuzzy set is suggested, which is subjected to the constraint conditions of fuzzy Cmeans cluster algorithm. The cluster fuzzy degree and the lattice degree of approaching for cluster fuzzy set are defined and their functions in validation process of fuzzy clustering are deeply analyzed. A new cluster validity function is presented, in which two factors, the cluster fuzzy degree and the lattice degree of approaching, are taken into account comprehensively. Furthermore, the detailed steps are given to apply the cluster validity function to the clustering validity for the fuzzy Cmeans cluster algorithm. The experimental results indicate the effectiveness and robustness of the proposed cluster validity function.
Key wordsCluster Analysis      Cluster Validity Function      Fuzzy CMeans Clustering     
Received: 12 January 2007     
ZTFLH: TP391  
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CHEN Duo
LI Xue
CUI DuWu
FEI Rong
Cite this article:   
CHEN Duo,LI Xue,CUI DuWu等. Cluster Validity Function Based on Fuzzy Degree[J]. , 2008, 21(1): 34-41.
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