A Novel Loss Function-based Support Vector Machine for Binary Classification

arXiv:2403.16654v1 Announce Type: new
Abstract: The previous support vector machine(SVM) including $0/1$ loss SVM, hinge loss SVM, ramp loss SVM, truncated pinball loss SVM, and others, overlooked the degree of penalty for the correctly classified samples within the margin. This oversight affects the generalization ability of the SVM classifier to some extent. To address this limitation, from the perspective of confidence margin, we propose a novel Slide loss function ($\ell_s$) to construct the support vector machine classifier($\ell_s$-SVM). By introducing the …

abstract arxiv binary classification classifier cs.lg function hinge loss machine math.oc novel oversight ramp samples support svm type vector