作　　者： ; ; ;

机构地区： 北京科技大学计算机与通信工程学院

出　　处： 《北京科技大学学报》 2006年第8期790-793,共4页

摘　　要： 提出了一种基于对偶优化的核最小二乘(KPLS)方法,把KPLS用最小二乘支持向量机的形式表示.推导了KPLS对偶优化形式的公式,且使其具有最小二乘支持向量机的风格.在初始空间中构造优化问题,应用核技术在特征空间中解对偶问题,这种解与非线性的KPLS具有相似性.实验验证了这种方法的效果,表明了该方法的有效性和优越性. A kernel partial least squares （KPLS） method based on dual optimization was proposed,which was expressed by least squares support vector machine. The KPLS formulae in the form of dual opti-mization were deduced, which had the style of least squares support vector machine. The optimization problem was constructed in a prime space, the dual problem was solved in a eigenspace by the kernel skill and the solutions were the same as nonlinear KPLS.

关 键 词： 优化问题 偏最小二乘 最小二乘支持向量机 核偏最小二乘

领　　域： [自动化与计算机技术] [自动化与计算机技术]