一种改进的支持向量机分类器

An improved support vector machine classifier

提出了一种将支持向量机分类和最近邻分类相结合的方法,形成了一种新的分类器。实验结果表明使用支持向量机结合最近邻分类的分类器分类比单独使用支持向量机分类具有更高的分类准确率,同时可以较好地解决应用支持向量机分类时核函数参数的选择问题。

This paper presented a mixed algorithm combining SVM with nearst neighbour classification to form a new classifier. The numerical experiments show that the mixed algorithm can not only improve the accuracy compared to sole SVM, but also better solve the problem of selecting the parameter of kernel function for SVM.