一种特殊支持向量回归机算法研究  

Research on a special support vector regression machine algorithm

作　　者：邵杰[1] 王强[1] 

机构地区：[1]山东科技大学,山东271019

出　　处：《信息技术》2009年第8期131-132,136,共3页Information Technology

摘　　要：支持向量机SVM(Support Vector Machines)是数据挖掘技术的新方法,支持向量回归机对函数拟合(回归逼近)具有重要的理论意义和应用价值。分别采用光滑化函数法和求解LC1函数类型方法对牛顿型算法进行研究求解。Support Vector Machine （SVM） is one of the new methods in data mining. Support vector regression machine has the important theoretical meaning and application value in function-fitting areas （regression approach）. In this paper, a special support vector regression machine algorithm is proposed, within which smoothing function and method to solve LC^1 type functions are combined to solve Newton-type algorithm.

关 键 词：支持向量机 回归算法 光滑化函数 牛顿型算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]