This document contains a general overview in the first few sections as well as a more detailed reference in later sections for SVMpython. If you re already familiar with SVMpython, it s possible to get a pretty good idea of how to use the package mer

有基于 matlav的svm软件工具，感觉挺好用的。里面有很多实例，稍加修改就可以使用。例如三分类问题： 1、输入三类数据xapp yapp 2、选择多类分类方法（一对多或一对一或m-svm） 3、设置参数 4、调用训练函数得到向量机参数 5、输入测试数据，得到预期结果。 -There is matlav based on the SVM-based software tools, I feel pretty useless. Inside there is a lot

这里实现了四种SVM工具箱的分类与回归算法 1、工具箱：LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱：OSU_SVM3.00 Classification_OSU_SVM.m - 多类分类 3、工具箱：stprtool\svm Classification_stprtool.m - 多类分类 4、工具箱：SVM_SteveGunn Classification_SVM_SteveGu

multiclass svm implemented code from online