Performs a crossvalidation on a given data set with nominal label, using a Support Vector Machine as a learning algorithm. Inside the cross validation, the first subprocess generates an SVM model, and the second subprocess evaluates it. applying it on a so-far unused subset of the data and counting the misclassifications.