It is supposed that the farther the positive and negative examples are separated by the discrimination function, the more accurately we could separate unseen test examples with high generalization performance.
let us consider two hyperplanes called separating hyperplanes: (2) (3) can be written in one formula as: Distance from the separating hyperplane to the point xi can be written as: the margin between two separating hyperplanes can be written as: w,b;xi) xi ;Yi = l xi;yi=--i  To maximize this margin, we should minimize Hwll.