Matlab Support Vector Machine (SVM) for multi-classification

1, first, you need to complete the installation of MATLAB.
2, extract the Libsvm-3.17.zip and Drtoolbox.tar files to: libsvm-3.17 folder and Drtoolbox, and put in the MATLAB Toolbox installation directory,
For example: C:\Program files\matlab\r2014a\toolbox directory.
3, start Matlab.
4. Click Set Path under the File menu ... menu item to open the Set Path dialog box.
5. Click Add with Subfolders ... command button, go to the C:\Program Files\matlab\r2014a\toolbox\drtoolbox folder, click the OK button, and the MATLAB Search path list box to the right of the Set Path dialog box will add 3 search paths.
6, repeat the above operation, enter the C:\Program files\matlab\r2014a\toolbox\libsvm-3.17 folder, add the LIBSVM 11 search paths.
7. Click the Save button, and then click the Close button.
8, run: C:\Program files\matlab\r2014a\toolbox\libsvm-3.17 under the MAKE.M file. Then check to see if the Libsvmread.mexw32,libsvmwrite.mexw32,svmtrain.mexw32,svmpredict.mexw32 4 files are generated under the \libsvm-3.17\matlab directory. If yes, the LIBSVM MATLAB has been compiled successfully.
Ok.setup success!

Libsvm-3.17.zip and Drtoolbox.tar files: http://download.csdn.net/detail/bingecuilab/8633397 resources are divided into 1. Review resources to return points,

SVM implementation of the classification of MATLAB Source: http://www.eyesourcecode.com/thread-46124-1-1.html

Matlab Support vector Machine (SVM) for multi-classification