Learning an optimal naive Bayes classifier

Proceedings - International Conference on Pattern Recognition

Volumn 3, Issue , 2006, Pages 1236-1239

  Martfnez Arroyo, Miriam ^a   Sucar, L Enrique ^b  

^a Del PRI   (Mexico)

^b INSTITUTO NACIONAL DE ASTROFÍSICA   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); INFORMATION THEORY; PROBLEM SOLVING;

CLASSIFICATION ACCURACY; DISCRETIZATION;

LEARNING SYSTEMS;

EID: 34147179933     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.748     Document Type: Conference Paper

References (10)

1. H. Acosta-Mesa, B. Zitova, H. Rios-Figueroa, N. Cruz-Ramirez, A. Marin-Hernandez, R. Hernandez-Jim'enez, B. Cocotle-Ronzon, and E. Hernandez-Galicia. Cervical cancer detection using colposcopic images: a temporal approach. In Proc. Sixth International Conference on Computer Science (ENC'05), pages 158-164. IEEE, 2005.
2. J. Cheng and R. Greiner. Comparing bayesian network classifiers. Proceedings of the Fifteenth Conference on Uncertainty in Arifi cial intelligence, pages 101-108, 1999.
3. N. Friedman, D. Geiger, and M. Goldszmidt. Bayesian network classifiers. Machine Learning, 29:131-163, 1997.
4. N. Friedman and M. Goldszmidt. Discretizing continuous attributes while learning bayesian networks. 13th International Conference on Machine Learning (ICML), pages 157-165, 1996.
5. W. Lam and F. Bacchus. Learning bayesian belief netwoks: An aproach based on the mdl principle. Computational Intelligence, 10:269-293, 1994.
6. M. J. Pazzani. An iterative improvement approach for the discretization of numeric attributes in bayesian classifiers. KDD95, pages 228-233, 1995.
7. M. J. Pazzani. Searching for atribute dependencies in bayesian classifiers. In preliminary Papers of the Intelligence and Statistics, pages 424-429, 1996.
8. L. Sucar. Probabilistic reasoning in knowledge based vision systems. PhD dissertation, Imperial College of Science, Technology, and Medicine, London U.K., 1992.
9. J. Valdes, L. Molina, and N. Peris. An evolution strategies approach to the simultaneous discretization of numeric attributes in data mining. In Proc. of the World Congress on Evolutionary Computation, pages 1957-1964, Canberra, Australia, 2003. IEEE Press.
10. Y. Yang and G. Webb. A comparative study of discretization methods for naive-bayes classifiers. In Proc. of the Pacific Rim Knowledge Acquisition Workshop (PRKAW), 2002.