An improved genetic algorithm for robust fuzzy clustering with unknown number of clusters

Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Volumn , Issue , 2010, Pages

  Banerjee, Amit ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Cluster validity; Clustering tendency; FCM; Genetic algorithms; Robust clustering

Indexed keywords

CLUSTER VALIDITY; CLUSTERING TECHNIQUES; CLUSTERING TENDENCY; FCM; FITNESS FUNCTIONS; IMPROVED GENETIC ALGORITHMS; MULTI-OBJECTIVE GENETIC ALGORITHM; NOISY DATA; NUMBER OF CLUSTERS; POTENTIAL SOLUTIONS; REPRESENTATION SCHEMES; ROBUST CLUSTERING; ROBUST FUZZY CLUSTERING;

DATA PROCESSING; FUNCTION EVALUATION; GENETIC ALGORITHMS; LAKES;

CLUSTERING ALGORITHMS;

EID: 77956598277     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NAFIPS.2010.5548175     Document Type: Conference Paper

References (18)

1. R. N. Dave and R. Krishnapuram, "Robust clustering method: A unified view," IEEE Trans. Fuzzy Syst., vol. 5, pp. 270-293, 1997.
2. K.-L. Wu, M.-S. Yang, and J.-N. Hsieh, "Robust cluster validity indices," Pattern Recog., vol. 42, pp. 2541-2550, 2009.
3. A. Banerjee, "Robust fuzzy clustering as a multi-objective optimization procedure," in Proc. Annual Meeting of North American Fuzzy Inform. Process. Soc., Cincinnati, OH, Jun. 2009.
4. K. Deb, Multi-Objective Optimization using Evolutionary Algorithms. Chichester: Wiley, 2001.
5. M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization, New York: Wiley, 2000.
6. D.-X. Chang, X.-D. Zhang, and C.-W. Zheng, "A genetic algorithm with gene rearrangement for K-means clustering," Pattern Recog., vol. 42, pp. 1210-1222, 2009.
7. U. Maulik and I. Saha, "Modified differential evolution based fuzzy clustering for pixel classification in remote sensing imagery," Pattern Recog., vol. 42, pp. 2135-2149, 2009.
8. A. Mukhopadhyay, U. Maulik, and S. Bandhopadhyay, "Multiobjective genetic algorithm-based fuzzy clustering of categorical attributes," IEEE Trans. Evol. Comput., vol. 13, pp. 991-1005, 2009.
9. A. K. Jain and R. C. Dubes, Algorithms for Clustering Data. Englewood Cliffs, NJ: Prentice Hall, 1988.
10. B. Hopkins, "A new method of determining the type of distribution of plant individuals," Ann. Bot., vol. 18, pp. 213-226, 1954.
11. B. D. Ripley, "Modelling spatial patterns," J. Royal Statis. Soc., vol. B39, pp. 172-212, 1977.
12. A. Banerjee and R. N. Dave, "Validating clusters using the Hopkins statistic," in Proc. IEEE Int. Conf. Fuzzy Syst., Budapest, Hungary, Jul. 2004, pp. 149-153.
13. A. Banerjee and R. N. Dave, "A context sensitive crossover operator for clustering applications," unpublished.
14. R. J. Campello, E. R. Hruschka and V. S. Alves, "On the efficiency of evolutionary fuzzy clustering," J. Heuristics, vol. 15, pp. 43-75, 2009.
15. C. J. Merz and P. M. Murphy, UCI Repository of Machine Learning Databases [Online]. University of California, Irvine, CA, Available: http://www.ics.uci. edu/∼mlearn.
16. E. R. Hruschka and N. F. F. Ebecken, "A genetic algorithm for cluster analysis," Intell. Data Anal., vol. 7, pp. 15-25, 2003.
17. R. Kothari and D. Pitts, "On finding the number of clusters," Pattern Recog. Lett., vol. 20, pp. 405-416, 1999.
18. L. O. Hall and P. M. Kanade, "Swarm based fuzzy clustering with partition validity," in Proc. IEEE Int. Conf. Fuzzy Syst., Reno, NV, May 2005, pp. 991-995.