Determination of the number of components in gaussian mixtures using agglomerative clustering

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 3, Issue , 1997, Pages 1412-1417

  Medasani, S ^a   Krishnapuram, R ^a  

^a University of Missouri   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGGLOMERATIVE CLUSTERING; CLASSIFICATION RATES; EXPECTATION-MAXIMIZATION ALGORITHMS; GAUSSIAN MIXTURE DECOMPOSITIONS; GAUSSIAN MIXTURES; MIXTURE DECOMPOSITION; NUMBER OF COMPONENTS; OBJECTIVE FUNCTIONS;

CLASSIFICATION (OF INFORMATION); NEURAL NETWORKS; PATTERN RECOGNITION; RADIAL BASIS FUNCTION NETWORKS; ALGORITHMS; FUNCTIONS; PATTERN RECOGNITION SYSTEMS; STATISTICAL METHODS;

ALGORITHMS; PATTERN RECOGNITION;

AGGLOMERATIVE GAUSSIAN MIXTURE DECOMPOSITION ALGORITHMS; EXPECTATION MAXIMIZATION (EM) ALGORITHMS;

EID: 0030706837     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.614001     Document Type: Conference Paper

References (16)

1. B.S. Everitt and Hand, Finite Mixture Distributions, Chapman & Hall, London, England, 1981.
2. D.M.Titterington, A.F.M.Smith, and U.E.Markov, Statistical Analysis of Finite Mixture Distributions, John Wiley & sons, New York, 1985.
3. R.A. Redner and H.H. Walker, "Mixture Densities, Maximum Likelihood and the EM algorithm," SI AM Review, Vol. 26, no. 2, p. 195-239, April 1984.
4. A. P. Dempster, N.M. Laird, and D.B. Rubin, "Maximum Likelihood from incomplete data via the EM Algorithm,"/. Roy. Statist. Soc. B. no. 39, p. 1-38, 1977.
5. S. Haykin, Neural Networks a Comprehensive Foundation, Mcmillan College Publishing Company, New York, 1994.
6. S. Medasani, R. Krishnapuram and C. W. Caldwell, "Robust Gaussian Mixture Decomposition," to appear in the Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Orlando, October 1997.
7. H. Akaike, "A New Look at the Statistical Model Identification" , IEEE Transactions on Automatic Control, Vol. AC-19, No. 6, p. 716-723, December 1974.
8. A.P. Pentland and T. Darrell, "Cooperative Robust Estimation Using Layers of Support", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, No.5, p. 474-487, May 1995.
9. X. Zhuang, Y. Huang, K. Palaniappan, and J.S. Lee, "Gaussian Mixture Density Modeling, Decomposition and Applications," IEEE Transactions on Image Processing, Vol. 5, No. 9, p. 1293-1301, September 1996.
10. J. Jhang and J.W. Modestino, "A Model-Fitting Approach to Cluster Validation with Application to Stochastic Model-Based Image Segmentation," IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 12, no. 10, p. 1009-1017, October 1990.
11. R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis, John Wiley, New York, 1973.
12. Y. S. Choi and R. Krishnapuram, "Fuzzy and Robust Formulations of Maximum-Likelihood-Based Gaussian Mixture Decomposition," Proceedings of the IEEE Int. Conf. on Fuzzy Systems, New Orleans, September 1996.
13. H. Frigui and R. Krishnapuram, A robust clustering algorithm based on competitive agglomeration and soft rejection of outliers. In Proceedings of the IEEE Conf. on Computer Vision and Pattern Recognition, San Francisco, California, 1996.
14. J.C.Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981.
15. P.M.Murphy and D.W. Aha, UCI repository of machine learning databases, http:///www ics.ci. edu/~mlearn/MLRespository.html[, Department of Information and Computer Science, University of California-Irvine.
16. H. Wolberg and O.L.Mangasarian, "Multisurface method of pattern separation for medical diagnosis applied to breast cytology," Proceedings of the National Academy of sciences, (87)9193-9196, Dec 1990.