%0 Journal Article
%T Learning approach for neural network ensemble based on specimen reconstruct<br>基于样本重构的神经网络集成学习方法
%A GONG Wen-ke
%A LI Chang-he
%A SHI Zheng-hao
%A ZHAO Jie
%A <br>巩文科
%A 李长河
%A 石争浩
%A 赵洁
%J 计算机应用
%D 2006
%I 
%X Based the review of the research of neural network ensemble,a new negative correlation learning method was proposed,which was both easy to implement and had the less computation,the co-linearity problem was eliminated,the error of the neural network ensemble was reduced.In the end,gives an test to this method,which prove that the method can reduce the error of the neural network ensemble effectively and get an expected result.
%K neural network ensemble
%K negative correlation learning
%K specimen reconstruct<br>神经网络集成
%K 负相关学习
%K 样本重构
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=9CB5D8A1BAA0A3E6&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=B31275AF3241DB2D&sid=1658FDEF8AE04907&eid=95A5B7E5A2BF95B5&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=8