Robust support vector model based on bounded asymmetric elastic net loss for binary classification

ArXi:2603.06257v1 Announce Type: cross In this paper, we propose a novel bounded asymmetric elastic net ($L_{baen}$) loss function and combine it with the vector machine (SVM), resulting in the BAEN-SVM. The $L_{baen}$ is bounded and asymmetric and can degrade to the asymmetric elastic net hinge loss, pinball loss, and asymmetric least squares loss. BAEN-SVM not only effectively handles noise-contaminated data but also addresses the geometric irrationalities in the traditional