When using RBF kernel I think feature space is infinite dimensional space. With infinite dimensional features, I believe any training set can be classified. So I'm wondering why training error > 0 even then? Does smoothing factor occurs that?
I forgot to mention about the identical feature vectors and the opposite label. Please ignore that case.