ABSTRACT
The main purpose of this chapter is to show the theoretical foundation of C-support vector classification (C-SVC) by developing a relationship between C-SVC and the statistical learning theory (SLT). We start by an overview of SLT, followed by a description of the structural risk minimization (SRM) principle. Lastly, we show a conclusion given by our paper [186] that the decision function obtained by C-SVC is just one of the decision functions obtained by solving the optimization problem derived directly from the SRM principle.
