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1.下载libSVM工具包 http://pan.baidu.com/s/1bnGNTBT或者下载最新版的到http://www.csie.ntu.edu.tw/~cjlin/libsvm/ 2.解压缩后放在matlab的toolbox目录下 如我的目录C:\Program Files\MATLAB\R2012a\toolbox\libsvm 3.打开matlab,matlab的菜单 File->Set Path->add with subfolders(可直接用Add Folder)里,把C:\Program Files\MATLAB\R2011a\toolbox\libsvm\matlab目录也添加进去 4.在matlab中输入mex –setup >> mex -setup Welcome to mex -setup. This utility will help you set up a default compiler. For a list of supported compilers, see http://www.mathworks.com/support/compilers/R2012a/win64.html Please choose your compiler for building MEX-files: Would you like mex to locate installed compilers [y]/n? y Select a compiler: [1] Microsoft Visual C++ 2008 SP1 in C:\Program Files (x86)\Microsoft Visual Studio 9.0 [0] None Compiler: 1 Please verify your choices: Compiler: Microsoft Visual C++ 2008 SP1 Location: C:\Program Files (x86)\Microsoft Visual Studio 9.0 Are these correct [y]/n? y *************************************************************************** Warning: MEX-files generated using Microsoft Visual C++ 2008 require that Microsoft Visual Studio 2008 run-time libraries be available on the computer they are run on. If you plan to redistribute your MEX-files to other MATLAB users, be sure that they have the run-time libraries. *************************************************************************** Trying to update options file: C:\Users\Wind\AppData\Roaming\MathWorks\MATLAB\R2012a\mexopts.bat From template: C:\PROGRA~1\MATLAB\R2012a\bin\win64\mexopts\msvc90opts.bat Done . . . ************************************************************************** Warning: The MATLAB C and Fortran API has changed to support MATLAB variables with more than 2^32-1 elements. In the near future you will be required to update your code to utilize the new API. You can find more information about this at: http://www.mathworks.com/help/techdoc/matlab_external/bsflnue-1.html Building with the -largeArrayDims option enables the new API. ************************************************************************** 不同的电脑因为安装的vc版本不同可能会出现不同的结果 5.在matlab current Floder中进入libSVM下的matlab路径 在matlab中输入make 如果顺利的话,可以正确编译 6.测试是否安装 >>[heart_scale_label,heart_scale_inst] =libsvmread('heart_scale'); >>model = svmtrain(heart_scale_label, heart_scale_inst, '-c 1 -g 0.07'); * >>[predict_label, accuracy, dec_values] = svmpredict(heart_scale_label, heart_scale_inst, model); % 输出 Accuracy = 86.6667% (234/270) (classification) 证明已经配置完成
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