F-Measure or F1-score

The F-measure is a harmonic mean of precision and recall values. It measures both the precision and robustness of clustering algorithms. It also tries to equalize the participation of false negatives using the value of β. This can be calculated as follows:

Here β is the non-negative value. β=1 gives equal weight to precision and recall, β = 0.5 gives twice the weight to precision than to recall, and β = 0 gives no importance to recall.