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 Minimal Primal Dual SVM is used with SVM
regularization parameter C=1 and a Gaussian kernel of width 1.2 and the
precision parameter 1e-5. 

For more details on the MPD solver see 
 Kienzle, W. and B. Schölkopf: Training Support Vector Machines with Multiple
 Equality Constraints. Machine Learning: ECML 2005, 182-193. (Eds.) Carbonell,
 J. G., J. Siekmann, Springer, Berlin, Germany (11 2005)
