PSVM，LSVM和NLSVM三种SVM分类算法的比较

A Comparison Among Three Svm Classification Methods:PSVM,LSVM and NLSVM

支持向量机(SVM)是数据分类的强大工具,本文对三个分类算法进行了比较。这三个算法是最近SVM(PSVM),Lagrangian SVM(LSVM)和有限牛顿LSVM(NLSVM),比较了三个算法给出线性分类器的过程以及算法的速度和精度,提供了用SVM方法分类问题时的导向。

Support vector machines (SVMs) are powerful tools for providing solutions to classification.In this paper,the comparison among the three classification methods is conducted.The three methods are proximal support vector machine (PSVM),lagrangian support vector machine (LSVM)and finite newton lagrangian support vector machine (NLSVM).The comparison of their algorithm in generating a linear kernel classifier,accuracy and computational complexity is also given.The study provides some guidelines for choosing an appropriate one from three SVM classification methods in a classification problem.