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...

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Detalles Bibliográficos
Autores principales: Chu, Maoxiang, Liu, Xiaoping, Gong, Rongfen, Zhao, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
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

Internet

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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