The F-measure, also known as the F1-score, is widely used to assess the performance of classification algorithms. However, some researchers find it lacking in intuitive interpretation, questioning the appropriateness of combining two aspects of performance as conceptually distinct as precision and recall, and also questioning whether the harmonic mean is the best way to combine them. To ease this concern, we describe a simple transformation of the F-measure, which we call F* (F-star), which has an immediate practical interpretation.

翻译：F措施(又称F1-分数)被广泛用来评估分类算法的性能,然而,一些研究人员发现它缺乏直观的解释,质疑将概念上不同的两个方面的性能结合为精确和回忆这两个方面是否适当,并质疑调和性能是否是将两者结合起来的最佳方法。为了缓解这一关切,我们描述了F措施的简单转变,我们称之为F*(F-star),它有直接的实际解释。