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FIND OUT MOREF1-score
The F1-score is a measure used to assess the quality of binary classification problems as well as problems with multiple binary labels or multiple classes.
If you are looking to select a model based on a balance between precision and recall, don’t miss out on assessing your F1-scores!
Definition
F1-score is defined as the harmonic mean of the precision and recall:
\[\begin{array}{rcl} \text{F1-score} & = & 2 * \dfrac{\text{Precision * Recall}}{\text{Precision + Recall}} \\ \end{array}\]
Note that precision and recall have the same relative contribution to the F1-score.