An Improved Weighted Mixed Bayes Classification Model

Abstract:

Article Preview

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 et al., "An Improved Weighted Mixed Bayes Classification Model", Advanced Materials Research, Vols. 179-180, pp. 1260-1265, 2011

Online since:

January 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.