Generally, if the training set is representative of the whole dataset, a classifier with larger margin with respect to training set would have better generalisation performance.
if the training set is unrepresentative, we should take great care of the margin in the margin learning algorithms, because the maximal margin classifier learned from an unrepresentative training set may have poor generalisation performance as illustrated in Figure 1.