An Experimental Study of Classifier Filtering

摘要：

In classifier combination, some component classifiers may give wrong information. If the classification results of these classifiers are adopted by the combination algorithm, the final output will be wrong. So eliminating the component classifiers which give wrong information may improve the performance of the classifier combination algorithm. To distinguish this kind of algorithm, we call it classifier filtering. This paper presents an experimental study of classifier filtering. The experimental results on biometric data set show that classifier filtering method may improve the accuracy of the classifier combination algorithm effectively.

关键词： Pattern Recognition Information fusion Classifier combination

作者: Zhang Suoliang Zhang Tianshu Liu Ming Li Kunlun Yuan Baozong

作者单位: College of Electronic and Information Engineering, Hebei University, Baoding 071002, China 1College of Electronic and Information Engineering, Hebei University, Baoding 071002, China Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China

会议类型: 国际会议

会议名称: 2010 The IET 3rd International Conference on Wireless,Mobile & Multimedia Networks(第三届IET无线移动及多媒体网络国际会议 ICWMMN 2010)

会议地点: 北京

会议语种:英文

页码: 361-364

在线出版日期: 2010-09-26（万方平台首次上网日期，不代表论文的发表时间）