In this example a two-class support vector machine classifier is trained on a
toy data set and the trained classifier is used to predict labels of test
examples. As training algorithm LIBSVM is used with SVM regularization
parameter C=1 and a Gaussian kernel of width 1.2 and 10MB of kernel cache and
the precision parameter epsilon=1e-5.

For more details on LIBSVM solver see http://www.csie.ntu.edu.tw/~cjlin/libsvm/
