Robust support vector machines based on the rescaled hinge loss function
Xu, Guibiao1; Cao, Zheng2; Hu, Bao-Gang1; Principe, Jose C.2
2017-03-01
发表期刊PATTERN RECOGNITION
卷号63页码:139-148
文章类型Article
摘要The support vector machine (SVM) is a popular classifier in machine learning, but it is not robust to outliers. In this paper, based on the Correntropy induced loss function, we propose the resealed hinge loss function which is a monotonic, bounded and nonconvex loss that is robust to outliers. We further show that the hinge loss is a special case of the proposed resealed hinge loss. Then, we develop a new robust SVM based on the resealed hinge loss. After using the half-quadratic optimization method, we find that the new robust SVM is equivalent to an iterative weighted SVM, which can help explain the robustness of iterative weighted SVM from a loss function perspective. Experimental results confirm that the new robust SVM not only performs better than SVM and the existing robust SVMs on the datasets that have outliers, but also presents better sparseness than SVM.
关键词Support Vector Machine Robustness Rescaled Hinge Loss Half-quadratic Optimization
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patcog.2016.09.045
关键词[WOS]CLASSIFICATION ; MINIMIZATION ; RECOGNITION ; CORRENTROPY ; SIGNAL
收录类别SCI
语种英语
项目资助者NSFC(61273196) ; China Scholarship Council
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000389785900011
引用统计
被引频次:10[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13367
专题模式识别国家重点实验室_多媒体计算与图形学
作者单位1.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China
2.Univ Florida, CNEL, Dept Elect & Comp Engn, Gainesville, FL 32611 USA
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Xu, Guibiao,Cao, Zheng,Hu, Bao-Gang,et al. Robust support vector machines based on the rescaled hinge loss function[J]. PATTERN RECOGNITION,2017,63:139-148.
APA Xu, Guibiao,Cao, Zheng,Hu, Bao-Gang,&Principe, Jose C..(2017).Robust support vector machines based on the rescaled hinge loss function.PATTERN RECOGNITION,63,139-148.
MLA Xu, Guibiao,et al."Robust support vector machines based on the rescaled hinge loss function".PATTERN RECOGNITION 63(2017):139-148.
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