Version 3.23 released on July 15, 2018. It conducts some minor fixes. LIBSVM tools provides many extensions of LIBSVM. Please check it if you need some functions not supported in LIBSVM. We now have a nice page LIBSVM data sets providing problems in LIBSVM format. A practical guide to SVM classification is available now! (mainly written for beginners) We now have an easy script (easy.py) for users who know NOTHING about SVM. It makes everything automatic--from data scaling to parameter selection.
The parameter selection tool grid.py generates the following contour of cross-validation accuracy. To use this tool, you also need to install python and gnuplot.
使用方法：
1. windows cmd命令窗口
下载的libsvm包里面已经为我们编译好了（windows）。
进入libsvm\windows，可以看到这几个exe文件：
1.svm-predict: svmpredict test_file mode_file output_file 依照已经train好的model ，输入新的数据，并输出预测新数据的类别。
2.svm-scale: 有时候特征值的波动范围比较大需要对特征数据进行缩放，可以缩放到0--1之间（自己定义）。
3.svm-toy:似乎是图形界面，可以自己画点，产生数据等。
4.svm-train: svmtrain [option] train_file [model_file] train 会接受特定格式的输入，产生一个model 文件。
第一步：可以自己生成数据，使用svm-toy：
双击svm-toy，点击change可以在画布上画点：
