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=0.9 and the bias term in the classification rule
switched off and the precision parameter epsilon=1e-5 (duality gap).

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. 

