%0 Journal Article
%T A Classification Approach Based on Evolutionary Neural Networks<br>一种基于多进化神经网络的分类方法
%A SHANG Lin
%A WANG Jin-Gen
%A YAO Wang-Shu
%A CHEN Shi-Fu
%A <br>商琳
%A 王金根
%A 姚望舒
%A 陈世福
%J 软件学报
%D 2005
%I 
%X Classification is important in data mining and machine learning. In this paper, a classification approach based on evolutionary neural networks (CABEN) is presented, which establishes classifiers by a group of three-layer feed-forward neural networks. The neural networks are trained by an improving algorithm synthesizing modified Evolutionary Strategy and Levenberg-Marquardt optimization method. The class label of the identifying data can first be evaluated by each neural network, and the final classification result is obtained according to the absolute-majority-voting rule. Experimental results show that the algorithm CABEN is effective for the classification, and has the better performance in classification precision, stability and fault-tolerance comparing with the traditional neural network methods, Bayesian classifiers and decision trees, especially for the complex classification problems with many classes.
%K evolutionary computation
%K evolutionary strategy
%K neural network
%K classification<br>进化计算
%K 进化策略
%K 神经网络
%K 分类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=08D815D632F704FC&yid=2DD7160C83D0ACED&vid=7801E6FC5AE9020C&iid=9CF7A0430CBB2DFD&sid=209749DE0D716184&eid=39AB3D3C12DB6AFD&journal_id=1000-9825&journal_name=软件学报&referenced_num=6&reference_num=15