Neyman-Pearson Classification under High-Dimensional Settings

13 Aug 2015Anqi ZhaoYang FengLie WangXin Tong

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) paradigm was introduced in this context as a novel statistical framework for handling asymmetric type I/II error priorities... (read more)

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