A NOVEL FUZZY CLASSIFIER ENSEMBLE SYSTEM

摘要：

In this paper,a novel fuzzy classifier ensemble system is proplsed.This system can reduce subjective factor in building a fuzzy classifier,and improve the classification recognition rate and stability.Three proplsed approaches are introduced,namely,the approach of measuring generalization difference(GD)of classifier sssets to select individual classifiers,the approach of determining individual classifiers reliability by the proposed membership matrix,the approach of classifier ensemble.The proplsed systeM is evaluated with standard data sets.The comparison of experiments and the existed classifier ensemble systems.The experiment results show that the recognition rate of our proplsed system is higher than ones of other classifier ensemble systems.

关键词： Fuzzy classifier Classifier ensemble Classifier ensemble Classifiers reliability Generalization difference

作者: AI-MIN YANG LING-MIN JIANG XIN-GUANG LI YONG-MEI ZHOU

作者单位: School of Informatics,Guangdong University of Foreign Studies,Guangzhou 510420,China;School of Compu School of Informatics,Guangdong University of Foreign Studies,Guangzhou 510420,China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 3582-3587

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）