Microarray Data Classification Based on Evolutionary Multiple Classifier System

摘要：

Designing an evolutionary multiple classifier system (MCS) is a relatively new research area. In this paper, we propose a genetic algorithm (GA) based MCS for microarray data classification. We construct a feature poll with different feature selection methods first, and then a multi-objective GA is applied to implement ensemble feature selection process so as to generate a set of classifiers. When this GA stops, a set of base classifiers are generated. Here we use all the nondominated individuals in last generation to build an ensemble system and test the proposed ensemble method and the method that apply a classifier selection process to select proper classifiers from all the individuals in last generation. The experimental results show the proposed ensemble method is roubust and can lead to promising results.

关键词： multiple classifier system ensemble feature selection genetic algorithm

作者: ZhengGang Gu KunHong Liu

作者单位: Department of Computer Engineering, Jiangsu College of Information Technology, WuXi, 214100, China Department of Data Mining, Software School of Xiamen University, XiaMen 361005, China

会议类型: 国际会议

会议名称: 2011 3nd International Conference on Mechanical and Electronics Engineering(2011年第三届机械与电子工程国际会议 ICMEE2011)

会议地点: 合肥

会议语种:英文

页码: 2077-2080

在线出版日期: 2011-09-23（万方平台首次上网日期，不代表论文的发表时间）