A new Bayesian classification algorithm based on attribute reduction
- DOI
- 10.2991/icmmcce-15.2015.1How to use a DOI?
- Keywords
- Naive Bayesian classifier, attribute reduction,PCA, Attribute correlation coefficient
- Abstract
Naive Bayesian classifier is a simple and efficient classification method. However, the assumption of the independence of its attributes is difficult to be satisfied, which influences the classification performance. In this paper, a new classification algorithm is proposed, which is based on the attribute correlation coefficient and principal component analysis. By the algorithm, we can remove the attributes that are not related to the class, and make sure that the retained attributes are independent of each other. By removing redundant attributes, the obtained attribute subset meets the assumption of Naive Bayesian classifier, and ultimately improves the classification performance of Naive Bayesian classifier.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hongmei Nie AU - Jiaqing Zhou PY - 2015/12 DA - 2015/12 TI - A new Bayesian classification algorithm based on attribute reduction BT - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015 PB - Atlantis Press SP - 1 EP - 5 SN - 2352-538X UR - https://doi.org/10.2991/icmmcce-15.2015.1 DO - 10.2991/icmmcce-15.2015.1 ID - Nie2015/12 ER -