Stacked density estimation

Advances in Neural Information Processing Systems

Volumn , Issue , 1998, Pages 668-674

  Smyth, Padhraic ^a,c   Wolpert, David ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b NASA AMES RESEARCH CENTER   (United States)

^c CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEST MODEL; CROSS VALIDATION; DENSITY ESTIMATION; FINITE MIXTURE MODELING; KERNEL DENSITY ESTIMATORS; MULTIVARIATE DENSITY ESTIMATION; NON-PARAMETRIC;

COMPUTER SIMULATION;

EID: 84872441718     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Banfield, J. D., and Raftery, A. E., 'Model-based Gaussian and non-Gaussian clustering, ' Biometrics, 49, 803-821, 1993.
2. Breiman, L., 'Bagging predictors, ' Machine Learning, 26(2), 123-140, 1996a.
3. Breiman, L., 'Stacked regressions, ' Machine Learning, 24, 49-64, 1996b.
4. Chickering, D. M., and Heckerman, D., 'Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables, ' Machine Learning, in press.
5. Draper, D, 'Assessment and propagation of model uncertainty (with discussion), ' Journal of the Royal Statistical Society B, 57, 45-97, 1995.
6. Escobar, M. D., and West, M., Bayesian density estimation and inference with mixtures, J. Am. Stat. Assoc., 90, 577-588, 1995.
7. Jordan, M. I. and Jacobs, R. A., 'Hierarchical mixtures of experts and the EM algorithm, ' Neural Computation, 6, 181-214, 1994.
8. Madigan, D., and Raftery, A. E., 'Model selection and accounting for model uncertainty in graphical models using Occam's window, ' J. Am. Stat. Assoc., 89, 1535-1546, 1994.
9. Ormeneit, D., and Tresp, V., 'Improved Gaussian mixture density estimates using Bayesian penalty terms and network averaging, ' in Advances in Neural Information Processing 8, 542-548, MIT Press, 1996.
10. Ripley, B. D. 1994. 'Neural networks and related methods for classification (with discussion), ' J. Roy. Stat. Soc. B, 56, 409-456.
11. Smyth, P., 'Clustering using Monte-Carlo cross-validation, ' in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, Menlo Park, CA: AAAI Press, pp.126-133, 1996.
12. Titterington, D. M., A. F. M. Smith, U. E. Makov, Statistical Analysis of Finite Mixture Distributions, Chichester, UK: John Wiley and Sons, 1985.
13. Wolpert, D. 1992. 'Stacked generalization, ' Neural Networks, 5, 241-259.