论文标题
班级失衡对精确曲线曲线的影响
The Effect of Class Imbalance on Precision-Recall Curves
论文作者
论文摘要
在本说明中，我研究了分类器的精度如何取决于测试集中的阳性案例的比率$ r $，以及分类器的真实和假阳性率。这种关系允许预测Precision-Recall曲线将如何随$ R $变化，这似乎并不众所周知。它还允许预测$f_β$以及Flach和Kull（2015）的精确增益和召回量度随$ r $变化。
In this note I study how the precision of a classifier depends on the ratio $r$ of positive to negative cases in the test set, as well as the classifier's true and false positive rates. This relationship allows prediction of how the precision-recall curve will change with $r$, which seems not to be well known. It also allows prediction of how $F_β$ and the Precision Gain and Recall Gain measures of Flach and Kull (2015) vary with $r$.
