F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation

20 Apr 2015 Xiaohe Wu WangMeng Zuo Yuanyuan Zhu Liang Lin

The generalization error bound of support vector machine (SVM) depends on the ratio of radius and margin, while standard SVM only considers the maximization of the margin but ignores the minimization of the radius. Several approaches have been proposed to integrate radius and margin for joint learning of feature transformation and SVM classifier... (read more)

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METHOD TYPE
SVM
Non-Parametric Classification