Bayesian Ying-Yang machine, clustering and number of clusters

Pattern Recognition Letters

Volumn 18, Issue 11-13, 1997, Pages 1167-1178

  Xu, Lei ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Bayesian Ying Yang machine; Cluster analysis; Finite mixture; Number of clusters

Indexed keywords

ALGORITHMS; LEARNING SYSTEMS; NUMBER THEORY; SET THEORY; STATISTICS; VECTOR QUANTIZATION;

BAYESIAN YING-YANG MACHINE; MEAN SQUARE ERROR CLUSTERING ANALYSIS;

PATTERN RECOGNITION;

EID: 0031270958     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-8655(97)00121-9     Document Type: Article

References (9)

1. Dempster, A.P., Laird, N.M., Rubin, D.B., 1997. Maximum-likelihood from incomplete data via the EM algorithm. J. Roy. Statist. Soc. Ser. B 39, 1-38.
2. Devroye, L., 1987. A Course in Density Estimation. Birhhauser, Boston, MA.
3. Jain, A.K., Dubes, R.C., 1988. Algorithm for Clustering Data. Prentice-Hall, Englewood Cliffs, NJ.
4. Xu, L., 1995. YING-YANG machine: A Bayesian-Kullback scheme for unified learnings and new results on vector quantization, Keynote talk. In: Proc. Internat. Conf. on Neural Information Processing (ICONIP95), pp. 977-988.
5. Xu, L., 1996. How many clusters?: A YING-YANG machine based theory for a classical open problem in pattern recognition. Invited Talk. In: Proc. 1996 IEEE Internat. Conf. on Neural Networks, Vol. 3, pp. 1546-1551.
6. Xu, L., 1997a. Bayesian Ying-Yang system and theory as a unified statistical learning approach: (I) For unsupervised and semi-unsupervised learning. In: Amari, S., Kassabov, N. (Eds.), Brain-like Computing and Intelligent Information Systems. Springer, Berlin.
7. Xu, L., 1997b. Bayesian ying-yang system and theory as a unified statistical learning approach: (II) Supervised learning. In: Proc. Internat. Workshop on Theoretical Aspects of Neural Computation, Hong Kong, 26-28 May. Lecture Notes in Computer Science. Springer, Berlin.
8. Xu, L., 1997c. New advances on Bayesian ying-yang learning system with Kullback and non-Kullback separation functionals. In: Proc. 1997 IEEE Internat. Conf. on Neural Networks, Vol. III, pp. 1942-1947.
9. Xu, L., Krzyzak, A., Oja, E., 1993. Competitive learning for clustering analysis, RBF net and curve detection. IEEE Trans. Neural Networks 4 (4), 636-649.