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Support vector machine with quantile hyper-spheres for pattern classification
This paper formulates a support vector machine with quantile hyper-spheres (QHSVM) for pattern classification. The idea of QHSVM is to build two quantile hyper-spheres with the same center for positive or negative training samples. Every quantile hyper-sphere is constructed by using pinball loss ins...
Autores principales: | Chu, Maoxiang, Liu, Xiaoping, Gong, Rongfen, Zhao, Jie |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377146/ https://www.ncbi.nlm.nih.gov/pubmed/30768635 http://dx.doi.org/10.1371/journal.pone.0212361 |
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