A method to enhance the 'Possibilistic C-Means with repulsion' algorithm based on cluster validity index

Advances in Soft Computing

Volumn 34, Issue , 2006, Pages 77-87

  Wachs, Juan ^a   Shapira, Oren ^a   Stern, Helman ^a  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33845452357     PISSN: 16153871     EISSN: 18600794     Source Type: Book Series    
DOI: 10.1007/3-540-31662-0_6     Document Type: Article

References (11)

1. Jain, A. K. and Dubes, R. C. (1988), Algorithms for clustering data, Prentice Hall, New Jersey.
2. Zadeh, L. A. (1965), "Fuzzy Sets," Information and Control, vol. 8, pp. 338-353.
3. Bezdek, J. C., (1982), Pattern recognition with fuzzy objective function algorithms, Plenum Press, New York.
4. Krishnapuram, R. and Keller, J. (1993), "A possibilistic approach to clustering," IEEE Trans. Fuzzy Systems, vol. 1, pp. 98-110.
5. Timm, H., Borgelt, C. and Kruse, R. (2001), "Fuzzy cluster analysis with cluster repulsion," In Proc. of the European Symp. on Intelligent Tech., Hybrid Syst. and their implementation on Smart Adapt. Syst., Tenerife, Spain.
6. Krishnapuram, R. and Keller, J. (1996), "The Possibilistic C-Means algorithm: Insights and recommendations", IEEE Trans. Fuzzy Systems, vol. 4, pp. 385-393.
7. Barni, M., Cappellini V., and Mecocci, A. (1996), "Comments on 'A Possibilistic Approach to Clustering'," IEEE Trans. Fuzzy Systems, vol. 4, pp. 393-396.
8. Bezdek, J. C. and Pal, N. R. (1998), "Some New Indexes of Cluster Validity," IEEE Trans. on SMC, Part B, vol. 28, no. 3, pp. 301-315.
9. Dave, R. N. and Krishnapuram, R. (1997), "Robust clustering methods: A unified view," IEEE Trans. Fuzzy Systems, vol. 5 no. 2, pp. 270-293.
10. Fisher, R. (1936), "The use of multiple measurements in taxonomic problems," Annals of Eugenics, vol.7, no. 2, 179-188.
11. Merz, C. J. and Murphy, P. M. (1996), UCI Repository of Machine Learning Databases, http://www.ics.uci.edu/~mlearn/MLRepository.html, University of California, Department of Information and computer Science.