In this example a multi-class 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 LaRank algorithm is used with SVM
regularization parameter C=1 and a Gaussian kernel of width 2.1 and a precision
set to epsilon=1e-5.

For more details on LaRank see
   Bordes, A. and Bottou, L. and Gallinari, P. and Weston, J.
   Solving MultiClass Support Vector Machines with LaRank. ICML 2007.

