Fuzzy Linear Discriminant Analysis-guided maximum entropy fuzzy clustering algorithm

Pattern Recognition

Volumn 46, Issue 6, 2013, Pages 1604-1615

  Zhi, Xiao Bin ^a   Fan, Jiu Lun ^b   Zhao, Feng ^b  

^a XIDIAN UNIVERSITY   (China)

^b XI AN UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Fuzzy Linear Discriminant Analysis; Fuzzy scatter matrix; Maximum entropy fuzzy clustering algorithm; Optimal transformation matrix

Indexed keywords

ADAPTIVE SUBSPACES; BENCHMARK DATA; COHERENT FRAMEWORKS; DATA CLUSTERING; DATA SETS; DIMENSIONALITY REDUCTION; FUZZY EXTENSION; FUZZY PARTITION; HARD C-MEANS; HARD C-MEANS CLUSTERING ALGORITHMS; LINEAR DISCRIMINANT ANALYSIS; LINEAR DISCRIMINANTS; MAXIMUM ENTROPY; OPTIMAL TRANSFORMATION; OPTIMIZATION CRITERIA; SCATTER MATRIX; SOFT DECISION; STATISTICAL APPROACH;

FEATURE EXTRACTION; FUZZY CLUSTERING; LEARNING ALGORITHMS; LINEAR TRANSFORMATIONS; MAXIMUM ENTROPY METHODS; OPTIMIZATION;

CLUSTERING ALGORITHMS;

EID: 84873160774     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2012.12.007     Document Type: Article

References (38)

1. J.A. Hartigan Clustering Algorithms 1975 Wiley New York
2. E.W. Forgy Cluster analysis of multivariate data: efficiency vs. interpretability of classifications Biometrics 21 1965 768 769
3. J. MacQueen, Some methods for classification and analysis of multivariate observations, in: Fifth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, 1967, pp. 281-297.
4. E.H. Ruspini A new approach to clustering Information and Control 15 1969 22 32
5. J.C. Dunn A fuzzy relative of the ISODATA process and its use in detecting compact, well-separated clusters Journal of Cybernetics 3 1974 32 37
6. J.C. Bezdek Pattern Recognition with Fuzzy Objective Function Algorithms 1981 Plenum Press New York
7. F. Hoppner, F. Klawonn, R. Kruse, and T. Runkler Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition 1999 John Wiley & Sons Ltd. New York
8. J.L. Fan, W.Z. Zhen, and W.X. Xie Suppressed fuzzy c-means clustering algorithm Pattern Recognition Letters 24 9-10 2003 1607 1612
9. K.L. Wu, J. Yu, and M.S. Yang. A novel fuzzy clustering algorithm based on a fuzzy scatter matrix with optimality test Pattern Recognition Letters 26 5 2005 639 652
10. J. Yu Optimality test for generalized FCM and its application to parameter selection IEEE Transactions on Fuzzy Systems 13 1 2005 164 176
11. R.P. Li, M. Mukaidono, A maximum entropy approach to fuzzy clustering, in: Proceedings of the Fourth International Conference on Fuzzy Systems, 1995, pp. 2227-2232.
12. N.B. Karayiannis, MECA: Maximum Entropy Clustering Algorithm, in: Proceedings of the Third IEEE International Conference on Fuzzy Systems, 1994, pp. 630-635.
13. Z.H. Zhang, N.N. Zheng, and G. Shi Maximum-entropy clustering algorithm and its global convergence analysis Science in China Series E: Technological Sciences 44 1 2001 89 101
14. J. Yu, H.B. Shi, H.K. Huang, X.C. Sun, and Q.S. Cheng Counter examples to convergence theorem of maximum-entropy clustering algorithm Science in China Series F: Information Sciences 46 5 2003 321 326
15. S.J. Ren, and Y.D. Wang A proof of the convergence theorem of maximum-entropy clustering algorithm Science in China Series F: Information Sciences 53 6 2010 1151 1158
16. P. Mitra, C. Murthy, and S. Pal Unsupervised feature selection using feature similarity IEEE Transactions on Pattern Analysis and Machine Intelligence 24 3 2002 301 312
17. M.H.C. Law, M.A.T. Figueiredo, and A.K. Jain Simultaneous feature selection and clustering using mixture models IEEE Transactions on Pattern Analysis and Machine Intelligence 26 9 2004 1154 1166
18. F. De la Torre, T. Kanade, Discriminative cluster analysis, in: Proceedings of the 23rd International Conference on Machine Learning, ACM Press, New York, 2006, pp. 241-248.
19. C. Ding, L. Tao, Adaptive dimension reduction using discriminant analysis and K-means clustering, in: Proceedings of the 24th International Conference on Machine Learning, ACM Press, New York, 2007, pp. 521-528.
20. J.P. Ye, Z. Zhao, and M.R. Wu Discriminative K-means for Clustering, in: Proceedings of the 21st Advances in Neural Information Processing Systems 2007 MIT Press USA pp. 1649-1656
21. I.T. Jolliffe Principal Component Analysis 2nd edition 2002 Springer
22. M. Belkin, and P. Niyogi Laplacian eigenmaps for dimensionality reduction and data representation Neural Computation 15 6 2003 1373 1396
23. A.Y. Ng, M.I. Jordan, and Y. Weiss On spectral clustering: analysis and an algorithm, in: Proceedings of the 14th Advances in Neural Information Processsing Systems 2002 MIT Press USA pp. 849-856
24. J. Shi, and J. Malik Normalized cuts and image segmentation IEEE Transactions on Pattern Analysis and Machine Intelligence 22 8 2000 888 905
25. K. Fukunaga Statistical Pattern Recognition 2nd edition 1990 Academic Press
26. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman Eigenfaces vs. Fisherfaces: recognition using class specific linear projection IEEE Transactions Pattern Analysis and Machine Intelligence 19 7 1997 711 720
27. J.H. Friedman Regularized discriminant analysis Journal of the American Statistical Association 84 405 1989 165 175
28. S. Raudys, and R.P.W. Duin On expected classification error of the fisher linear classifier with pseudo-inverse covariance matrix Pattern Recognition Letters 19 5-6 1998 385 392
29. J. Ye, and T. Xiong Computational and theoretical analysis of null space and orthogonal linear discriminant analysis Journal of Machine Learning Research 7 2006 1183 1204
30. X.H. Wu, and J.J. Zhou. Fuzzy discriminant analysis with kernel methods Pattern Recognition 39 11 2006 2236 2239
31. W.K. Yang, J.G. Wang, M.W. Ren, L. Zhang, and J.Y. Yang Feature extraction using fuzzy inverse FDA Neurocomputing 72 13-15 2009 3384 3390
32. X.N. Song, Y.J. Zheng, X.J. Wu, X.B. Yang, and J.Y. Yang A complete fuzzy discriminant analysis approach for face recognition Applied Soft Computing 10 1 2010 208 214
33. D.J. Newman, S. Hettich, C.L. Blake, C.J. Merz, UCI repository of machine learning databases, 〈http://www.ics.uci.edu/mlearn/MLRepository. html〉, 1998.
34. M. Breitenbach, G. Grudic, Clustering through ranking on manifolds, in: Proceedings of the 22nd International Conference on Machine Learning, ACM Press, New York, 2005, pp. 73-80.
35. K.Y. Yeung, M. Medvedovic, and R.E. Bumgarner Clustering gene-expression data with repeated measurements Genome Biology 4 5 2003 R34
36. S. Pomeroy, P. Tamayo, M. Gaasenbeek, L. Sturla, M. Angelo, M. McLaughlin, J. Kim, L. Goumnerova, P. Black, and C. Lau Prediction of central nervous system embryonal tumor outcome based on gene expression Nature 415 2002 436 442
37. C.H. Li, B.C. Kuo, and C.T. Lin. LDA-based clustering algorithm and its application to an unsupervised feature extraction IEEE Transactions on Fuzzy Systems 19 1 2011 152 163
38. C. Bouveyron, and C. Brunet Simultaneous model-based clustering and visualization in the Fisher discriminative subspace Statistics and Computing 22 1 2012 301 324