hesela.devF1 score
F1 score is the harmonic mean of precision and recall for a specified positive class and decision threshold.
For binary predictions, F1 = 2TP / (2TP + FP + FN); true negatives do not enter this formula. If TP, FP and FN are all zero, it is undefined; report the software's zero-division convention. F1 is neither recall nor accuracy, and multiclass or multilabel results must state the averaging rule. [1] Separately averaged or median precision and recall do not generally reconstruct an averaged or median F1. [2]
Relations
- related
- precision, recall, false-positive-rate, class-prevalence, average-precision, temporal-validation
Limitations
- A single F1 value does not state how many healthy drives trigger alerts or the operational cost of false alarms; retain precision, recall, prevalence and the counting unit. [2]