Matlab implementation of the EM and MCMC algorithm for SVMs as introduced in the paper Data augmentation for support vector machines http://ba.stat.cmu.edu/journal/2011/vol06/issue01/polson.pdf-This is a Matlab implementation of the fancy idea by Polson & Scott that reformulates the traditional binary linear SVM problem into a MAP (Maximum a Posteriori) estimation in a probabilistic generative model, and by use of the technique of data augmentation, makes it possible to do very easy and fast Gibbs sampling for the solution.