  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.
