School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Genome Biol. 2024 May 13;25(1):118. doi: 10.1186/s13059-024-03266-y.
The precision-recall curve (PRC) and the area under the precision-recall curve (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluate 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in more than 3000 published studies. We find the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.
精准召回曲线(PRC)和精准召回曲线下面积(AUPRC)可用于量化分类性能。它们常用于不平衡类情况,例如癌症诊断和细胞类型注释。我们评估了 10 种用于绘制 PRC 和计算 AUPRC 的流行工具,这些工具在 3000 多个已发表的研究中被共同使用。我们发现,这些工具计算的 AUPRC 值对分类器的排名不同,并且一些工具产生了过于乐观的结果。