Boosting the tree augmented naive bayes classifier

Downs, T. and Tang, A. L. T. (2004). Boosting the tree augmented naive bayes classifier. In: Z. Yang, R. Everson and H. Yin, Intelligent Data Engineering and Automated Learning: IDEAL 2004. The Fifth International Intelligent Data Engineering and Automated Learning Conference (IDEAL), Exeter, U.K., (708-713). 25-27 August 2004.


Author Downs, T.
Tang, A. L. T.
Title of paper Boosting the tree augmented naive bayes classifier
Conference name The Fifth International Intelligent Data Engineering and Automated Learning Conference (IDEAL)
Conference location Exeter, U.K.
Conference dates 25-27 August 2004
Proceedings title Intelligent Data Engineering and Automated Learning: IDEAL 2004   Check publisher's open access policy
Journal name Intelligent Daa Engineering and Automated Learning Ideal 2004, Proceedings   Check publisher's open access policy
Place of Publication Berlin, Germany
Publisher Springer
Publication Year 2004
Sub-type Fully published paper
ISBN 3-540-22881-0
ISSN 0302-9743
Editor Z. Yang
R. Everson
H. Yin
Volume 3177
Start page 708
End page 713
Total pages 6
Collection year 2004
Language eng
Abstract/Summary The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the Naïve Bayes approach by taking account of conditional probabilities. It does this in a limited sense, by incorporating the conditional probability of each attribute given the class and (at most) one other attribute. The method of boosting has previously proven very effective in improving the performance of Naïve Bayes classifiers and in this paper, we investigate its effectiveness on application to the TAN classifier.
Subjects E1
280207 Pattern Recognition
700101 Application packages
Q-Index Code E1
Additional Notes Series title: Lecture Notes in Computer Science

 
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Created: Thu, 23 Aug 2007, 19:46:53 EST