Principal weighted support vector machines for sufficient dimension reduction in binary classification

Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods may work poorly for binary classification. For example, sliced inverse regression (Li, 1991) can estimate at most one direction if the response is binary. In...

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Detalles Bibliográficos
Autores principales: Shin, Seung Jun, Wu, Yichao, Zhang, Hao Helen, Liu, Yufeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793677/
https://www.ncbi.nlm.nih.gov/pubmed/29430027
http://dx.doi.org/10.1093/biomet/asw057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793677/
https://www.ncbi.nlm.nih.gov/pubmed/29430027
http://dx.doi.org/10.1093/biomet/asw057

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