A new Bayesian classification algorithm based on attribute reduction
- Hongmei Nie, Jiaqing Zhou
- Corresponding Author
- Hongmei Nie
Available Online December 2015.
- https://doi.org/10.2991/icmmcce-15.2015.1How to use a DOI?
- Naive Bayesian classifier, attribute reduction,PCA, Attribute correlation coefficient
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
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 - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icmmcce-15.2015.1 DO - https://doi.org/10.2991/icmmcce-15.2015.1 ID - Nie2015/12 ER -