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 the LIBSVM solver is used with SVM
regularization parameter C=1 and a Gaussian kernel of width 2.1 and the
precision parameter epsilon=1e-5. The example also shows how to retrieve the
support vectors from the train SVM model.

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