%0 Journal Article
%T Structure risk minimization based weighted partial least-squared method<br>基于结构风险最小化的加权偏最小二乘法
%A BAI Yi-feng
%A XIAO Jian
%A YU Long
%A HUANG Jing-chun
%A <br>白裔峰
%A 肖建
%A 于龙
%A 黄景春
%J 计算机应用
%D 2007
%I 
%X Weighted Partial Least-Squared (WPLS) method was proposed to achieve Structure Risk Minimization(SRM)in the Partial Least-Squares (PLS) modeling process.At first,WPLS abstracted the principal components of training samples,and then it trained the weight of samples by means of Support Vector Machine (SVM) algorithm,and finally computed the regression model in the original universe discourse.WPLS not only takes the advantage of PLS to extract most explanatory variables,but also improves generalization property through the weight of samples and SRM is achieved with interpretable model.Simulation results show the effectiveness of the proposed method.
%K Structure Risk Minimization (SRM)
%K Weighted Partial Least-Squares (WPLS)
%K Support Vector Machine (SVM)
%K interpretability<br>结构风险最小化
%K 加权偏最小二乘法
%K 支持向量机
%K 可解释性
%K 结构风险
%K 最小化
%K 加权
%K 乘法
%K method
%K partial
%K weighted
%K based
%K minimization
%K risk
%K 有效性
%K 仿真计算
%K 可解释性
%K 准则
%K 泛化能力
%K 回归模型
%K 训练样本
%K 信息
%K 系统
%K 训练算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=A90A914025802A9F4EC41B06CC50BE02&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=E158A972A605785F&sid=384C451D3BE0C38C&eid=27A5865B8C0B85C3&journal_id=1001-9081&journal_name=计算机应用&referenced_num=1&reference_num=10