In this example a two-class linear 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 OCAS solver is used with the SVM
regularization parameter C=1.2 and the bias term in the classification rule
switched off. The solver iterates until the relative duality gap falls below
epsilon=1e-5 or the maximal training time (max_train_time=60 seconds) is
exceeded.

For more details on the OCAS solver see
 V. Franc, S. Sonnenburg. Optimized Cutting Plane Algorithm for Large-Scale Risk
 Minimization.The Journal of Machine Learning Research, vol. 10,
 pp. 2157--2192. October 2009.

