Bayesian feature and model selection for Gaussian mixture models

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 28, Issue 6, 2006, Pages 1013-1018

  Constantinopoulos, Constantinos ^a   Titsias, Michalis K ^b   Likas, Aristidis ^a  

^a UNIVERSITY OF IOANNINA   (Greece)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Bayesian approach; Feature selection; Mixture models; Model selection; Variational training

Indexed keywords

LEARNING ALGORITHMS; MATHEMATICAL MODELS; OPTIMIZATION; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

BAYESIAN APPROACH; FEATURE SELECTION; VARIATIONAL TRAINING;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; NORMAL DISTRIBUTION; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED;

EID: 33645957324     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2006.111     Document Type: Article

References (12)

1. B.G. McLachlan and D. Peel, Finite Mixture Models. Wiley, 2000.
2. P. Carbonetto, N. de Freitas, P. Gustafson, and N. Thompson, "Bayesian Feature Weighting for Unsupervised Learning, with Application to Object Recognition," Proc. Ninth Int'l Conf. Artificial Intelligence and Statistics, 2003.
3. M.H. Law, M.A.T. Figueiredo, and A.K. Jain, "Simultaneous Feature Selection and Clustering Using a Mixture Model," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 9, pp. 1154-1166, Sept. 2004.
4. J. Dy and C. Brodley, "Feature Selection for Unsupervised Learning," J. Machine Learning Research, vol. 5, pp. 845-889, 2004.
5. R.M. Neal and G.E. Hinton, "A View of the EM Algorithm that Justifies Incremental, Sparse, and Other Variants," Learning in Graphical Models, M.I. Jordan, ed., pp. 355-368, Kluwer, 1998.
6. H. Attias, "A Variational Bayesian Framework for Graphical Models," Advances in Neural Information Processing Systems 12, MIT Press, 2000.
7. A. Corduneanu and C.M. Bishop, "Variational Bayesian Model Selection for Mixture Distributions," Proc. Eighth Int'l Conf. Artificial Intelligence and Statistics, T. Richardson and T. Jaakkola, eds., pp. 27-34, Morgan Kaufmann, 2001.
8. J.S. Liu, J.L. Zhang, M.J. Palumbo, and C.E. Lawrence, "Bayesian Clustering with Variable and Transformation Selections," Bayesian Statistics, vol. 7, pp. 249-276, 2003.
9. J.H. Friedman and J.J. Meulman, "Clustering Objects on Subsets of Attributes," J. Royal Statistical Soc., vol. 66, no. 4, pp. 815-849, 2004.
10. P.D. Hoff, "Model-Based Subspace Clustering," Bayesian Analysis, vol. 1, no. 2, pp. 321-344, 2006.
11. A.K. Jain, R. Duin, and J. Mao, "Statistical Pattern Recognition: A Review," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-38, Jan. 2000.
12. C.L. Blake and C.J. Merz, "UCI Repository of Machine Learning Databases," 1998, http://www.ics.uci.edu/mlearn/MLRepository.html.