Kernel-Free Quadratic Surface Support Vector Regression with Non-Negative Constraints

In this paper, a kernel-free quadratic surface support vector regression with non-negative constraints (NQSSVR) is proposed for the regression problem. The task of the NQSSVR is to find a quadratic function as a regression function. By utilizing the quadratic surface kernel-free technique, the model...

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Detalles Bibliográficos
Autores principales: Wei, Dong, Yang, Zhixia, Ye, Junyou, Yang, Xue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378113/
https://www.ncbi.nlm.nih.gov/pubmed/37509977
http://dx.doi.org/10.3390/e25071030

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378113/
https://www.ncbi.nlm.nih.gov/pubmed/37509977
http://dx.doi.org/10.3390/e25071030

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