Margin Preserved Approximate Convex Hulls for Classification

The usage of convex hulls for classification is discussed with a practical algorithm, in which a sample is classified according to the distances to convex hulls. Sometimes convex hulls of classes are too close to keep a large margin. In this paper, we discuss a way to keep a margin larger than a specified value. To do this, we introduce a concept of "expanded convex hull" and confirm its effectiveness.