Alternative prior assumptions for improving the performance of naïve Bayesian classifiers

Data Mining and Knowledge Discovery

Volumn 18, Issue 2, 2009, Pages 183-213

  Wong, Tzu Tsung ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Conjugate; Dirichlet assumption; Generalized Dirichlet distribution; Liouville distribution; Na ve Bayesian classifier

Indexed keywords

BAYESIAN NETWORKS; CLASSIFIERS;

CONFIDENCE LEVELS; CONJUGATE; DATA SETS; DIRICHLET ASSUMPTION; DIRICHLET DISTRIBUTIONS; GENERALIZED DIRICHLET DISTRIBUTION; LIOUVILLE DISTRIBUTION; MULTIVARIATE DISTRIBUTIONS; PRIOR DISTRIBUTIONS; RANDOM VECTORS;

LEARNING SYSTEMS;

EID: 60849091358     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-008-0101-6     Document Type: Article

References (19)

1. Aitchison J (1986) The statistical analysis of compositional data. John Wiley, New York
2. Anderson DR, Sweeney DJ, Williams TA, Chen JC (2006) Statistics for business and economics: a practical approach, Chap. 7, Thomson Learning
3. VM Bier W Yi 1995 A Bayesian method for analyzing dependencies in precursor data Int J Forecast 11 25 41
4. Blake C, Merz C (1998) UCI machine learning repository, http://www.ics.uci.edu/~mlearn/MLRepository.html.
5. Cestnik B, Bratko I (1991) On estimating probabilities in tree pruning. Machine Learning-EWSL-91, European Working Session on Learning. Springer-Verlag, Berlin, Germany, pp 138-150
6. RJ Connor JE Mosimann 1969 Concepts of independence for proportions with a generalization of the Dirichlet distribution J Am Stat Assoc 64 194 206
7. P Domingos M Pazzani 1997 On the optimality of the simple Bayesian classifier under zero-one loss Mach Learn 29 103 130
8. Dougherty J, Kohavi R, Sahami M (1995) Supervised and unsupervised discretization of continuous features. In: Proceedings of the 12th international conference on machine learning. Morgan Kaufmann, San Francisco, CA, pp 194-202
9. Fang KT, Kotz S, Ng KW (1990) Symmetric multivariate and related distributions. Chapman and Hall, New York
10. CN Hsu HJ Huang TT Wong 2003 Implications of the Dirichlet assumption for discretization of continuous attributes in naïve Bayesian classifiers Mach Learn 53 235 263
11. H Ishwaran LF James 2001 Gibbs sampling methods for stick-breaking priors J Am Stat Assoc 96 161 173
12. Kohavi R, Sahami M (1996) Error-based and entropy-based discretization of continuous features. In: Proceedings of the second international conference on knowledge discovery and data mining, Portland, OR, pp 114-119
13. Langley P, Iba W, Thompson K (1992) An analysis of Bayesian classifiers. AI Research Branch, NASA Ames Research Center, Moffett Field, CA 94035, USA
14. RH Lochner 1975 A generalized Dirichlet distribution in Bayesian life testing J Roy Stat Soc Series B 37 103 113
15. Mitchell TM (1997) Machine learning. McGraw-Hill
16. Wilks SS (1962) Mathematical Statistics. John Wiley, New York
17. TT Wong 1998 Generalized Dirichlet distribution in Bayesian analysis Appl Math Comput 97 165 181
18. TT Wong 2005 A Bayesian approach employing generalized Dirichlet priors in predicting microchip yields J Chin Inst Ind Eng 22 210 217
19. TT Wong 2007 Perfect aggregation of Bayesian analysis on compositional data Stat Papers 48 265 282