Squared Hinge Loss
Squared Hinge Loss is a loss function in machine learning that belongs to the class of margin-based loss functions, distinguished by its formulation as the squared positive part of the difference between one and the product of the true label and the predicted score, thereby penalizing misclassifications more severely than the standard hinge loss.
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1.5K
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105
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2017–2026
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Robust support vector machines based on the rescaled hinge loss function
Guibiao Xu, Zheng Cao, Bao-Gang Hu et al. · Pattern Recognition · 2016 · 116 citations
Linear dimensionality reduction for multi-label classification
Shuiwang Ji, Jieping Ye · 2009 · 88 citations
A Study on L2-Loss (Squared Hinge-Loss) Multiclass SVM
Ching-pei Lee, Chih‐Jen Lin · Neural Computation · 2013 · 78 citations
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Nanyang Technological University
Singapore, Singapore
3 h-index
7 publications
349 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
4 publications
274 citations

Northwestern Polytechnical University
Xi'an, China
2 h-index
2 publications
80 citations
École Normale Supérieure
Bujumbura, Burundi
2 h-index
2 publications
37 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
2 h-index
4 publications
61 citations

Sun Yat-sen University
Guangzhou, China
2 h-index
5 publications
124 citations
The University of Texas at Arlington
Arlington, United States
2 h-index
4 publications
160 citations

University of Birjand
Birjand, Iran
1 h-index
1 publications
11 citations
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3 publications · 204 citations
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Repository · 3 publications · 58 citations
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3 publications · 76 citations
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2 publications · 126 citations
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