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npcs

Neyman-Pearson Classification via Cost-Sensitive Learning

v0.1.1 · Apr 27, 2023 · GPL-2

Description

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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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies dfoptim magrittr smotefamily foreach caret formatR dplyr forcats ggplot2 tidyr nnet npcs

Version History

new 0.1.1 Mar 9, 2026