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资源说明：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.
本源码包内暂不包含可直接显示的源代码文件，请下载源码包。
