In this example a two-class linear support vector machine classifier is trained
on a toy data set and the trained classifier is then used to predict labels of
test examples. As training algorithm the LIBLINEAR solver is used with the SVM
regularization parameter C=0.9 and the bias in the classification rule switched
on and the precision parameters epsilon=1e-5.

For more details on LIBLINEAR see
    http://www.csie.ntu.edu.tw/~cjlin/liblinear/
