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npcs: Neyman-Pearson Classification via Cost-Sensitive Learning
We connect the multi-class Neyman-Pearson classification (NP) problem to the cost-sensitive learning (CS) problem, and propose two algorithms (NPMC-CX and NPMC-ER) to solve the multi-class NP problem through cost-sensitive learning tools. Under certain conditions, the two algorithms are shown to satisfy multi-class NP properties. More details are available in the paper "Neyman-Pearson Multi-class Classification via Cost-sensitive Learning" (Ye Tian and Yang Feng, 2021).
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Package details |
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| Author | Ye Tian [aut], Ching-Tsung Tsai [aut, cre], Yang Feng [aut] |
| Maintainer | Ching-Tsung Tsai <tctsung@nyu.edu> |
| License | GPL-2 |
| Version | 0.1.1 |
| Package repository | View on CRAN |
| Installation |
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