A Hybrid Generative/Discriminative Bayesian Classifier

Changsung Kang, Jin Tian

In this paper, we introduce a new restricted Bayesian network classifier that extends naive Bayes by relaxing the conditional independence assumptions, and show that it is partly generative and partly discriminative. Experimental results show that the hybrid classifier performs better than a purely generative classifier (naive Bayes) or a purely discriminative classifier (Logistic Regression) and has performance comparable to some state-of-the-art classifiers.

Subjects: 12. Machine Learning and Discovery

Submitted: Feb 12, 2006


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