北京科技大学学报2012，Vol.34Issue(6)：718-725,8.
基于样条函数的光滑支持向量机模型
Smooth support vector machine model based on spline functions
摘要
Abstract
Differentiable and unconstrained quadratic programming can be constructed by improving a support vector machine （SVM） model using a smooth function, and thus a lot of fast optimization algorithms can be applied to solve the smooth SVM model. A new five-order spline function and a new seven-order spline function were constructed by a general three-moment method. These two spline functions are proved that their approximation accuracy is better than any other smooth functions, and the convergence accuracy of the spline function SVM model based on the five-order spline or seven-order spline is higher than any other smooth SVM models.关键词
支持向量机/样条/分类/数值方法收敛性Key words
support vector machines/splines/classification/convergence of numerical methods分类
信息技术与安全科学引用本文复制引用
张晓丹,邵帅,刘钦圣..基于样条函数的光滑支持向量机模型[J].北京科技大学学报,2012,34(6):718-725,8.
