Introducing a margin parameter into the SVM, which led to a new learning algorithm -the SVM with uneven margins, is a strategy for the SVM to deal with some kind of poor quality of training examples.
if we want to use the SVM to solve a very unbalanced binary classification problem where only a few positive training examples are available and are very unlikely to be representative, a larger positive margin in the SVM classifier should be beneficial to the generalisation performance of the SVM, as we argued in Section 3.