Asada, Takeshi; Yun, Yeboon; Nakayama, Hirotaka; … - In: Computational Management Science 1 (2004) 3, pp. 211-230
Support Vector Machines (SVMs) are now very popular as a powerful method in pattern classification problems. One of main features of SVMs is to produce a separating hyperplane which maximizes the margin in feature space induced by nonlinear mapping using kernel function. As a result, SVMs can...