Libsvm3.17很好用的分类和回归Matlab代码，亲测可用

libsvm-3.17实现分类测试特征向量的功能

libsvm-3.17.zip 支持向量机svm

支持向量机源码，可在 www.csie.ntu.edu.tw/~cjlin/libsvm/ 下载到最新版本，该版本是 2013年4月更新的，3.17 版。压缩包里面有源代码和文档。以下摘自前述网站： Introduction LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification. Since version 2.8, it implements an SMO-type algorithm proposed in this paper: R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM) Our goal is to help users from other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include Different SVM formulations Efficient multi-class classification Cross validation for model selection Probability estimates Various kernels (including precomputed kernel matrix) Weighted SVM for unbalanced data Both C++ and Java sources GUI demonstrating SVM classification and regression Python, R, MATLAB, Perl, Ruby, Weka, Common LISP, CLISP, Haskell, OCaml, LabVIEW, and PHP interfaces. C# .NET code and CUDA extension is available. It's also included in some data mining environments: RapidMiner, PCP, and LIONsolver. Automatic model selection which can generate contour of cross valiation accuracy.

MATLAB的SVM安装包drtoolbox与libsvm-3.17安装包。 在MATLAB中使用支持向量机，需要使用这两个文件。