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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Association for the Advancement of Science
2018
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| 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 |