Generalized noise clustering as a robust fuzzy c-M-estimators model

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

Volumn , Issue , 1998, Pages 256-260

  Davé, Rajesh N ^a   Sen, Sumit ^a  

^a NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; INFORMATION TECHNOLOGY;

DATA PARTITIONING; FEATURE VECTORS; M-ESTIMATORS; MODE SEEKING; NOISE CLUSTERING; POSSIBILISTIC; ROBUST FUZZY; TUKEY BIWEIGHT;

CLUSTERING ALGORITHMS;

EID: 0344006411     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NAFIPS.1998.715576     Document Type: Conference Paper

References (18)

1. M. Barni, V. Cappellini, and A. Mecocci "Comments on A Possibilistic Approach to Clustering" IEEE Transactions on Fuzzy Systems. 4, 393-396, 1996.
2. J. Bezdek. Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum, 1981.
3. K. K. Chintalpudi, "A Noise Resistant Fuzzy c-Means", to appear, Seventh IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'98), May 1998.
4. R. N. Dave. "Characterization and Detection of Noise in Clustering". Pattern Recognition Letters, vol. 12 (11), pp. 657-664, 1991.
5. R. N. Davé and R. Krishnapurum. "M-estimators and Robust Fuzzy Clustering". Proc. Biennial Conference of the North American Fuzzy Information Processing Society 1996, Berkeley, CA, 1996, pp. 400-404.
6. R. N. Dave and R. Krishnapurum. "Robust Clustering Methods: A Unified View". IEEE Trans. Fuzzy Systems, 270-293, 1997.
7. R. N. Dave and Sumit Sen, "On Generalizing the Noise Clustering Algorithms", An Invited Paper, Seventh IFSA World Congress:IFSA '97, Vol. III., pp. 205-210, Prague, June 25-29, 1997
8. R. N. Dave and Sumit Sen, "Noise Clustering Algorithm Revisited", Proc. Biennial Wrokshop of the North American Fuzzy Information Processing Society 1997, Syracuse, NY, pp. 199-204, 1997.
9. F. Hampel, E. M. Ronchetti, P. J. Rousseeuw, and W. A. Stahel. Robust Statistics: The Approach Based on Influence Functions. John Wiley & Sons, New York, 1986.
10. P. Huber. "Robust estimation of a location parameter". Ann. Math. Statist. A (6), 789-794, 1964.
11. P. Huber. Robust Statistics. John Wiley & Sons, New York, 1981.
12. R. Krishnapuram and J. M. Keller. "A Possibilistic Approach to Clustering". IEEE Transactions on Fuzzy Systems. 1 (2), 98-110, 1993.
13. R. Krishnapuram and J. M. Keller. "The Possibilistic C-Means Algorithm: Insights and Recommendations". IEEE Transactions on Fuzzy Systems. 4, 385-393, 1996.
14. N. Pal, J. Bezdek, and K. Pal, "A Mixed c-means Clustering Model", Sixth IEEE International Conference on Fuzzy Systems (FUZZ-IEEE '97), Vol. I, pp. 11-22, Barcelona, Spain, July 1-5, 1997.
15. P. J. Rousseeuw and A. M. Leroy. Robust Regression and Outlier Detection. John Wiliey & Sons, New York, 1987.
16. J-P Tarel, "Geometric Fuzzy Clustering: a generic Approach," submitted to IEEE Transactions on Fuzzy Systems, 1996.
17. M. P. Windham, "Numerical classification of proximity data with assignment measures," J. of Classification, vol. 2, pp. 157-172, 1985.
18. H.-J. Zimmerman and P. Zysno, "Quantifying Vagueness in Decision Models," European J. Operational Res., vol. 22, pp. 148-158, 1985.