Human chromosome classification using competitive support vector machine teams

Abstract

Classification of chromosome is a challenging task and requires very precise autonomous classifier. This paper proposes to employ competing support vector machines (SVMs) placed in a grid. Each agent in cells of the grid is responsible to distinguish two classes. Overall output is determined by simple majority voting of SVMs. Relying same principle as the work by Palalic and Can [17], we compared the results obtained where the algorithms delivers better accuracy.