Neyman-pearson classiffication under high-dimensional settings

Neyman-pearson classiffication under high-dimensional settings

Most existing binary classification methods target on the optimization of the overall classification risk and may fail to serve some real-world applications such as cancer diagnosis, where users are more concerned with the risk of misclassifying one specific class than the other. Neyman-Pearson (NP)...

Полное описание

Библиографические подробности
Главные авторы:	Zhao, Anqi, Feng, Yang, Wang, Lie, Tong, Xin
Другие авторы:	Massachusetts Institute of Technology. Department of Mathematics
Формат:	Статья
Опубликовано:	JMLR, Inc. 2018
Online-ссылка:	http://hdl.handle.net/1721.1/116907 https://orcid.org/0000-0003-3582-8898

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