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| Cluster Validity Function Based on Fuzzy Degree |
| CHEN Duo1,2, LI Xue1,3, CUI DuWu1, 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 Cmeans 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 Cmeans cluster algorithm. The experimental results indicate the effectiveness and robustness of the proposed cluster validity function.
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Received: 12 January 2007
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2008, Vol. 21 
