Paper Title:
An Improved Weighted Mixed Bayes Classification Model
  Abstract

The paper investigates kinds of classical Bayes classification arithmetic and summarizes their advantage and disadvantage, then introduces an improved weighted mixed Bayes classification model. It divides attribute sets into several subsets theorem. The subsets are trained by TAN (Tree Augmented Naive Bayes) and the results are integrated by weighted formula. At the same, the paper introduced a new method to compute the weights of attribute subsets. Finally, Experimental results show that this model has higher classification accuracy and practicability.

  Info
Periodical
Advanced Materials Research (Volumes 179-180)
Edited by
Garry Zhu
Pages
1260-1265
DOI
10.4028/www.scientific.net/AMR.179-180.1260
Citation
W. X. Xu, L. Y. Sun, X. M. Liu, "An Improved Weighted Mixed Bayes Classification Model", Advanced Materials Research, Vols. 179-180, pp. 1260-1265, 2011
Online since
January 2011
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Price
$32.00
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