Naïve Bayes variants in classification learning

Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10

Volumn , Issue , 2010, Pages 276-281

  Al Aidaroos, Khadija Mohammad ^a   Abu Bakar, Azuraliza ^a   Othman, Zalinda ^a  

^a UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Classification learning; Na ve Bayes (NB) classifier; NB variants

Indexed keywords

BAYESIAN CLASSIFIER; CLASSIFICATION ALGORITHM; CLASSIFICATION LEARNING; INDEPENDENCE ASSUMPTION; LOCAL LEARNING; NAIVE BAYES;

INFORMATION RETRIEVAL; KNOWLEDGE MANAGEMENT;

CLASSIFIERS;

EID: 77953887312     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INFRKM.2010.5466902     Document Type: Conference Paper

References (31)

1. N. Friedman, D. Geiger, and M. Goldszmidt, "Bayesian Network Classifiers," Machine Learning, 1997. 29(2-3): pp. 131-163.
2. I. Rish, "An Empirical Study of the Naïve Bayes Classifier," In: Proceedings of the Int. Joint Conf. on Artificial Intelligence, Workshop on "Empirical Methods in AI", 2001.
3. F. Zheng and G. I. Webb, "A Comparative Study of Semi-naïve Bayes Methods in Classification Learning," Proceeding 4th Australasian Data Mining conference (AusDM05), 2005: pp. 141-156.
4. P. Domingos and M. Pazzani, "On the Optimality of the Simple Bayesian Classifier under Zero-One Loss," Machine Learning, 1997. 29(2-3): pp. 103-130.
5. E. Frank, M. Hall, and B. Pfahringer, "Locally Weighted Naive Bayes," In: Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2003: pp. 249-256. Morgan Kaufmann.
6. Y. Ji and L. Shang, "RoughTree: A Classifier with Naïve-Bayes and Rough Sets Hybrid in Decision Tree Representation," 2007 IEEE International Conference on Granular Computing, 2007: pp. 221-226.
7. S.B. Kotsiantis, I.D. Zaharakis, and P.E. Pintelas, "Machine Learning: A Review of Classification and Combining Techniques," Artificial Intelligence Review, 2006. 26(3): pp. 159-190.
8. B. Liu, Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Data-Centric Systems and Applications. 2007: Springer.
9. R. Kohavi, "Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid," in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining. 1996: pp. 202-207.
10. I. Zelič, I. Kononenko, N. Lavrač, and V. Vuga, "Induction of Decision Trees and Bayesian Classification Applied to Diagnosis of Sport Injuries," Journal of Medical Systems, 1997. 21(6): pp. 429-444.
11. R. Abraham, J.B. Simha, and S.S. Iyengar, "Medical Datamining with a New Algorithm for Feature Selection and Naïve Bayesian Classifier," in ICIT. 2007: IEEE Computer Society, pp.44-49.
12. Z. Xie, W. Hsu, Z. Liu, and M. Lee, "SNNB: A Selective Neighborhood Based Naive Bayes for Lazy Learning," Lecture Notes in Computer Science, 2002: pp. 104-114.
13. P. Langley and S. Sage, "Induction of Selective Bayesian Classifiers," in Proceedings of the 10th Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann. 1994: pp. 399-406.
14. C.A. Ratanamahatana and D. Gunopulos, "Scaling up the Naive Bayesian Classifier: Using Decision Trees for Feature Selection," in Proceedings of Workshop on Data Cleaning and Preprocessing (DCAP 2002), IEEE International Conference on Data Mining (ICDM 2002).
15. F. Zheng and G. I. Webb, "Efficient Lazy Elimination for Averaged One-Dependence Estimators," in Proceedings of the 23rd International Conference on Machine Learning, 2006: pp. 1113-1120.
16. Y. Yang and G. I. Webb, "On why discretization works for naive- Bayes classifiers," Lecture Notes in Computer Science, 2003: pp. 440-452.
17. R. Abraham, J.B. Simha and S.S. Iyengar, "A Comparative Analysis of Discretization Methods for Medical Data Mining with Naïve Bayesian Classifier," in 9th International Conference on Information Technology (ICIT'06), 2006: pp. 235-236.
18. J. Dougherty, R. Kohavi, and M. Sahami, "Supervised and Unsupervised Discretization of Continuous Features," in Proc. 12th International Conference on Machine Learning. 1995: Morgan Kaufmann.
19. L.-M. Wang, X.-L. Li, C.-H. Cao and S.-M. Yuan, "Combining Decision Tree and Naïve Bayes for Classification," Knowledge-Based Systems, 2006. 19(7): pp. 511-515.
20. U. M. Fayyad and K. B. Irani, "Multi-interval Discretization of Continuous-valued Attributes for Classification Learning," in Proceedings of the 13th International Joint Conference on Artificial Intelligence, 1993: pp. 1022-1027.
21. M. Sahami, "Learning Limited Dependence Bayesian Classifiers," in KDD-96 Proceedings, AAAI Press. 1996: pp. 335-338.
22. Z. Zheng and G.I. Webb, "Lazy Learning of Bayesian Rules," Machine Learning, 2000. 41(1): pp. 53-84.
23. Z. Wang and G. I. Webb, "A Heuristic Lazy Bayesian Rule Algorithm," The Australasian Data Mining Workshop, 2002.
24. H. Zhang and S. Sheng, "Learning Weighted Naïve Bayes with Accurate Ranking," in Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM'04), 2004.
25. L. Jiang and Y. Guo, "Learning Lazy Naive Bayesian Classifiers for Ranking," in Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI. 2005: pp. 412-416.
26. G.I. Webb, J. Boughton, and Z. Wang, "Not so Naive Bayes: Aggregating One-Dependence Estimators," Machine Learning, 2005. 58(1): pp. 5-24.
27. L. Jiang, H. Zhang and Z. Cai, "Dynamic K-Nearest-Neighbor Naive Bayes with Attribute Weighted," in FSKD. LNCS, 2006: Springer. pp. 365-368.
28. Z. Qin, "Naïve Bayes Classification Given Probability Estimation Trees," in Proceedings of the 5th International Conference on Machine Learning and Applications (ICMLA'06), 2006.
29. M. Hall, "A Decision Tree-Based Attribute Weighting Filtering for Naïve Bayes," Knowledge-Based Systems, 2007. 20(2): pp. 120-126.
30. Z. Pawlak, "Rough Sets and Intelligent Data Analysis," Information Sciences, Elsevier. 2002: pp. 1-12.
31. A. Skowron, "Rough Sets in KDD," in Proceedings of the 16th World Computer Congress (IFIP'2000). 2000: pp. 1-14.