F*: an interpretable transformation of the F-measure

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.

Automated summary

The F-measure, also known as the F1-score, is commonly used to evaluate classification algorithms, but some researchers question its intuitive interpretation and the combination of precision and recall. To address this concern, a simple transformation called F* (F-star) with practical interpretation has been introduced.