An information-theoretic filter approach for value weighted classification learning in naive Bayes

Author:

Lee Chang-Hwan

Funder

Korea Research Foundation

Ministry of Trade, Industry&Energy

Publisher

Elsevier BV

Subject

Information Systems and Management

Reference28 articles.

1. Z. Zheng, G.I. Webb, Lazy learning of bayesian rules, in: Machine Learning, Kluwer Academic Publishers, 2000, pp. 53–84.

2. R. Kohavi, Scaling up the accuracy of naive-bayes classifiers: A decision-tree hybrid, in: Proceedings of the Second International Conference on Knoledge Discovery and Data Mining, 1996.

3. A review and empirical evaluation of feature weighting methods for a class of lazy learning algorithms;Wettschereck;Artif. Intell. Rev.,1997

4. P. Domingos, M. Pazzani, On the optimality of the simple bayesian classifier under zero-one loss, Machine Learning 29 (2–3).

5. T. Gärtner, P.A. Flach, Wbcsvm: Weighted bayesian classification based on support vector machines, in: Proceedings of the Eighteenth International Conference on Machine Learning, 2001.

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