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Neyman-Pearson classification algorithms and NP receiver operating characteristics

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this...

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Detalles Bibliográficos
Autores principales: Tong, Xin, Feng, Yang, Li, Jingyi Jessica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5804623/
https://www.ncbi.nlm.nih.gov/pubmed/29423442
http://dx.doi.org/10.1126/sciadv.aao1659

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