In this example a two-class support vector machine classifier is trained on a
DNA splice-site detection data set and the trained classifier is used to predict
labels on test set. As training algorithm SVM^light is used with SVM
regularization parameter C=1.2 and the Weighted Degree kernel of degree 20 and
the precision parameter epsilon=1e-5.

For more details on the SVM^light see
 T. Joachims. Making large-scale SVM learning practical. In Advances in Kernel
 Methods -- Support Vector Learning, pages 169-184. MIT Press, Cambridge, MA USA, 1999.

For more details on the Weighted Degree kernel see
 G. Raetsch, S.Sonnenburg, and B. Schoelkopf. RASE: recognition of alternatively
 spliced exons in C. elegans. Bioinformatics, 21:369-377, June 2005. 
