%0 Journal Article
%T A Regression SVM Selection Ensemble Approach<br>一种回归SVM选择性集成方法
%A ZHANG Yu
%A WANG Wen-Jian
%A KANG Xiang-Ping
%A <br>张妤
%A 王文剑
%A 康向平
%J 计算机科学
%D 2008
%I 
%X Generalization performance is a basic problem for machine learning, and ensemble learning technique can improve the generalization performance effectively. This paper presents a selective ensemble learning approach based on SVM regression. By introducing three threshold parameters, some component SVM can be chose, and the efficiency of the whole ensemble learning system can be further improved. Simulation results demonstrate the presented approach can solve model selection and learning for large-scale dates...
%K Support vector machine
%K Ensemble learning
%K Regression
%K Bagging<br>支持向量机
%K 集成学习
%K 回归
%K Bagging
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=386B1A134552E0FF144CAC1226215F34&yid=67289AFF6305E306&vid=6209D9E8050195F5&iid=E158A972A605785F&sid=4609832E4B5C797B&eid=F1A8654ADB4E656E&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=10