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Abstract
We investigate a simple semi-naive Bayesian ranking method that combine naive Bayes with induction of decision tables. Naive Bayes and decision tables can both be trained efficientyly, and the same holds true for the combined semi-naive model. We show that the resulting ranker, compared to either component technique, frequently significantly increases AUC. For some datasets it significantly improves on both techniques. This is also the case when attribute selection is performed in naive Bayes and its semi-naive variant.
Type
Conference Contribution
Type of thesis
Series
Citation
Hall, M. & Frank, E.(2008). Combining Naive Bayes and Decision Tables. In D.L. Wilson & H. Chad (Eds), Proceedings of Twenty-First International Florida Artificial Intelligence Research Society Conference, AAAI Press, Coconut Grove, Florida, USA, 15-17 May, 2008(pp. 318-319).
Date
2008
Publisher
AAAI Press
Degree
Supervisors
Rights
This is an article published in Proceedings of Twenty-First International Florida Artificial Intelligence Research Society Conference, AAAI Press, Coconut Grove, Florida, USA, 15-17 May, 2008.