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 Gradient Projection Decomposition Technique
(GPDT) is used with SVM regularization parameter C=1.2 and a Gaussian
kernel of width 2.1 and 10MB of kernel cache. 

For more details on GPDT solver see http://dm.unife.it/gpdt 
 
   
