a classification method that works on the principle of fitting a boundary to a region of points that are all alike
makes classifications by defining a decision boundary and then seeing what side of the boundary an unclassified point falls on
produce models that generalize well, by maximizing the margin between the decision boundary and and the nearest element of each class.