Evolutionary fuzzy Ccustering: An overview and efficiency issues

Studies in Computational Intelligence

Volumn 204, Issue , 2009, Pages 167-195

  Horta, D ^a   Naldi, M ^a   Campello, R J G B ^a   Hruschka, E R ^a   Carvalho, A C P L F ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 65549135889     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-01088-0_8     Document Type: Review

References (60)

1. Alves, V.S., Campello, R.J.G.B., Hruschka, E.R.: A Fuzzy Variant of an Evolutionary Algorithm for Clustering. In: Proc. IEEE Int. Conference on Fuzzy Systems, pp. 375-380 (2007)
2. Arabie, L.J., Hubert, G., DeSoete, P.: Clustering and Classification. World Scientific, Singapore (1999)
3. Babu, G.P., Murty, M.N.: Clustering with Evolution Strategies. Pattern Recognition 27, 321-329 (1994)
4. Babuška, R.: Fuzzy Modeling for Control. Kluwer, Dordrecht (1998)
5. Baldi, P., Brunak, S.: Bioinformatics - The Machine Learning Approach, 2nd edn. MIT Press, Cambridge (2001)
6. Bertone, P., Gerstein, M.: Integrative Data Mining: The New Direction in Bioinformatics - Machine Learning for Analyzing Genome-Wide Expression Profiles. IEEE Engineering in Medicine and Biology 20, 33-40 (2001)
7. Bezdek, J.C., Pal, N.R.: Some new indexes of cluster validity. IEEE Trans. on Systems, Man and Cybernetics - B 28, 301-315 (1998)
8. Bezdek, J.C., Hathaway, R.J.: Optimization of Fuzzy Clustering Criteria using Genetic Algorithms. In: Proc. IEEE World Congress on Computational Intelligence, pp. 589-594 (1994)
9. Bezdek, J.C., Hathaway, R.J., Howard, R.E., Wilson, C.A., Windham, M.P.: Local Convergence Analysis of a Grouped Variable Version of Coordinate Descent. Journal of Optimization Theory and Applications 54, 471-477 (1987)
10. Bezdek, J.C., Hathaway, R.J., Sabin, M.J., Tucker, H.T.: Convergence Theory for Fuzzy C-Means: Counterexamples and Repairs. IEEE Trans. on Systems, Man and Cybernetics SMC-17, 873-877 (1987)
11. Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithm. Plenum Press (1981)
12. Bigus, J.P.: Data Mining with Neural Networks. McGraw-Hill, New York (1996)
13. Campello, R.J.G.B., Alves, V.S., Hruschka, E.R.: On the Efficiency of Evolutionary Fuzzy Clustering. Journal of Heuristics, doi:10.1007/ s10732-007-9059-6
14. Campello, R.J.G.B., Hruschka, E.R.: A Fuzzy Extension of the Silhouette Width Criterion for Cluster Analysis. Fuzzy Sets and Systems 157(21), 2858-2875 (2006)
15. Davis, L.: Handbook of Genetic Algorithms. International Thomson Computer Press (1996)
16. de Oliveira, J.V., Pedrycz, W.: Advances in Fuzzy Clustering and its Applications. Wiley, Chichester (2007)
17. Egan, M.A., Krishnamoorthy, M., Rajan, K.: Comparative Study of a Genetic Fuzzy C-Means Algorithm and a Validity Guided Fuzzy C-Means Algorithm for Locating Clusters in Noisy Data. In: Proc. IEEE World Congress on Computational Intelligence, pp. 440-445 (1998)
18. Everitt, B.S., Landau, S., Leese, M.: Cluster Analysis. Arnold Publishers (2001)
19. Falkenauer, E.: Genetic Algorithms and Grouping Problems. John Wiley & Sons, Chichester (1998)
20. Fazendeiro, P., Valente de Oliveira, J.: A Semantic Driven Evolutive Fuzzy Clustering Algorithm. In: Proc. IEEE Int. Conference on Fuzzy Systems, pp. 1-6 (2007)
21. Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. IEEE Press, New York (1995)
22. Fogel, D.B., Simpson, P.K.: Evolving Fuzzy Clusters. In: Proc. IEEE Int. Conference on Neural Networks, pp. 1829-1834 (1993)
23. Fralley, C., Raftery, A.E.: How Many Clusters? Which Clustering Method? Answer via Model-Based Cluster Analysis. The Computer Journal 41, 578-588 (1998)
24. Freitas, A.: A Review of Evolutionary Algorithms for Data Mining. In: Maimon, O., Rokach, L. (eds.) Soft Computing for Knowledge Discovery and Data Mining, pp. 61-93. Springer, Heidelberg (2007)
25. Ghozeil, A., Fogel, D.B.: Discovering Patterns in Spatial Data using Evolutionary Programming. In: Proc. 1st Annual Conference on Genetic Programming, pp. 521-527 (1996)
26. Halkidi, M., Batistakis, Y., Vazirgiannis, M.: On Clustering Validation Techniques. Journal of Intelligent Information Systems 17, 107-145 (2001)
27. Hall, L.O., Bezdek, J.C., Boggavarpu, S., Bensaid, A.: Genetic Fuzzy Clustering. In: Proc. Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS), pp. 411-415 (1994)
28. Hall, L.O., Özyurt, B.: Scaling Genetically Guided Fuzzy Clustering. In: Proc. Int. Symposium on Uncertainty Modeling and Analysis & Annual Conference of the North American Fuzzy Information Processing Society (ISUMA-NAFIPS), pp. 328-332 (1995)
29. Hall, L.O., Özyurt, I.B., Bezdek, J.C.: Clustering with a Genetically Optimized Approach. IEEE Trans. on Evolutionary Computation 3, 103-112 (1999)
30. Höppner, F., Klawonn, F., Kruse, R., Runkler, T.: Fuzzy Cluster Analysis: Methods for Classification. In: Data Analysis and Image Recognition. Wiley, Chichester (1999)
31. Hruschka, E.R., Campello, R.J.G.B., de Castro, L.N.: Clustering Gene-Expression Data: A Hybrid Approach that Iterates between k-Means and Evolutionary Search. In: Grosan, C., Abraham, A., Ishibuchi, H. (eds.) Hybrid Evolutionary Algorithms, pp. 313-335. Springer, Heidelberg (2007)
32. Hruschka, E.R., Campello, R.J.G.B., de Castro, L.N.: Evolutionary Search for Optimal Fuzzy C-Means Clustering. In: Proc. Int. Conference on Fuzzy Systems, pp. 685-690 (2004)
33. Hruschka, E.R., Campello, R.J.G.B., de Castro, L.N.: Evolving Clusters in Gene-Expression Data. Information Sciences 176, 1898-1927 (2006)
34. Hruschka, E.R., Campello, R.J.G.B., Freitas, A.A., Carvalho, A.C.P.L.F.: A Survey of Evolutionary Algorithms for Clustering. IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews (to appear)
35. Hruschka, E.R., de Castro, L.N., Campello, R.J.G.B.: Evolutionary Algorithms for Clustering Gene-Expression Data. In: Proc. 4th IEEE Int. Conference on Data Mining, pp. 403-406 (2004)
36. Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs (1988)
37. Jain, A.K., Murty, M.N., Flynn, P.J.: Data Clustering: A Review. ACM Computing Surveys 31, 264-323 (1999)
38. Jiang, D., Tang, C., Zhang, A.: Cluster Analysis for Gene Expression Data: A Survey. IEEE Trans. on Knowledge and Data Engineering 16, 1370-1386 (2004)
39. Kaufman, L., Rousseeuw, P.J.: Finding Groups in Data - An Introduction to Cluster Analysis. Wiley Series in Probability and Mathematical Statistics (1990)
40. Klawonn, F.: Fuzzy Clustering with Evolutionary Algorithms. In: Proc. of 7th Int. Fuzzy Systems Association (IFSA) World Congress, pp. 312-323 (1997)
41. Kolen, J.F., Hutcheson, T.: Reducing the Time Complexity of the Fuzzy C-Means Algorithm. IEEE Trans. on Fuzzy Systems 10, 263-267 (2002)
42. Liu, H., Li, J., Chapman, M.A.: Automated Road Extraction from Satellite Imagery using Hybrid Genetic Algorithms and Cluster Analysis. Journal of Environmental Informatics 1(2), 40-47 (2003)
43. Liu, J., Xie, W.: A Genetics-Based Approach to Fuzzy Clustering. In: Proc. Int. Conference on Fuzzy Systems, pp. 2233-2240 (1995)
44. MacQueen, J.B.: Some Methods of Classification and Analysis of Multivariate Observations. In: Proc. 5th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281-297 (1967)
45. Maulik, U., Bandyopadhyay, S.: Fuzzy Partitioning Using Real Coded Variable Length Genetic Algorithm for Pixel Classification. IEEE Trans. on Geosciences and Remote Sensing 41(5), 1075-1081 (2003)
46. Mecca, G., Raunich, S., Pappalardo, A.: A New Algorithm for Clustering Search Results. Data and Knowledge Engineering 62, 504-522 (2007)
47. Milligan, G.: A Monte Carlo Study of Thirty Internal Criterion Measures for Cluster Analysis. Psychometrika 46(2), 187-199 (1981)
48. Milligan, G.W., Cooper, M.C.: An Examination of Procedures for Determining the Number of Clusters in a Data Set. Psychometrika 50, 159-179 (1985)
49. Pakhira, M.K., Bandyopadhyay, S., Maulik, U.: A Study of some Fuzzy Cluster Validity Indices, Genetic Clustering and Application to Pixel Classification. Fuzzy Sets and Systems 155, 191-214 (2005)
50. Pal, N.R., Bezdek, J.C.: On Cluster Validity for the Fuzzy c-Means Model. IEEE Transactions on Fuzzy Systems 3(3) (1995)
51. Pantel, P.A.: Clustering by Commitee, PhD Thesis, Department of Computer Sciences of the University of Alberta, Canada (2003)
52. Park, H.-S., Yoo, S.-H., Cho, S.-B.: Evolutionary Fuzzy Clustering Algorithm with Knowledge-Based Evaluation and Applications for Gene Expression Profiling. Journal of Computational and Theoretical Nanoscience 2, 1-10 (2005)
53. Rayward-Smith, V.J.: Metaheuristics for Clustering in KDD. In: Proc. IEEE Congress on Evolutionary Computation, pp. 2380-2387 (2005)
54. Rezaee, M.R., Lelieveldt, B.P.F., Reiber, J.H.C.: A New Cluster Validity Index for the Fuzzy c-Mean. Pattern Recognition Letters 19, 237-246 (1998)
55. Srikanth, R., George, R., Warsi, N., Prabhu, D., Petry, F.E., Buckles, B.P.: A Variable-Length Genetic Algorithm for Clustering and Classification. Pattern Recognition Letters 16, 789-800 (1995)
56. Sun, H., Wang, S., Jiang, Q.: FCM-Based Model Selection Algorithms for Determining the Number of Clusters. Pattern Recognition Letters 37, 2027-2037 (2004)
57. Valafar, F.: Pattern Recognition Techniques in Microarray Data Analysis: A Survey. Annals of New York Academy of Sciences 980, 41-64 (2002)
58. Van Le, T.: Evolutionary Fuzzy Clustering. In: Proc. IEEE Congress on Evolutionary Computation, pp. 753-758 (1995)
59. Xu, R., Wunsch II, D.: Survey of Clustering Algorithms. IEEE Trans. on Neural Networks 16, 645-678 (2005)
60. Yuan, B., Klir, G.J., Swan-Stone, J.F.: Evolutionary Fuzzy C-Means Clustering Algorithm. In: Proc. Int. Conference on Fuzzy Systems, pp. 2221-2226 (1995)