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Fuzzy Systems and Knowledge Discovery, Fourth International Conference on (2007)
Haikou, Hainan, China
Aug. 24, 2007 to Aug. 27, 2007
ISBN: 0-7695-2874-0
pp: 608-612
Congxin Jiao , Nanjing University
Jiangwen Sun , Nanjing University
Chongjun Wang , Nanjing University
Manwu Xu , Nanjing University
ABSTRACT
This paper proposes a new classification approach; we call the Graph Augmented Bayes classifier (GAB). We show that naive Bayes classifier is a special case of GAB under the conditional independence assumption. GAB relaxes the conditional independence assumptions and takes into account of the influences on an attribute from all other attributes, and extends naive Bayes with the capability in expressiveness of non-linearly separable concepts. We conduct experiments by using datasets from the University of California at the Irvine repository. The experimental results show that the classifier extends naive Bayes with significant improvement in accuracy.
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CITATION

C. Jiao, C. Wang, M. Xu and J. Sun, "GAB: Graph Augmented Bayes Classifier," 2007 International Conference on Fuzzy Systems and Knowledge Discovery(FSKD), Haikou, 2007, pp. 608-612.
doi:10.1109/FSKD.2007.340
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