F1 score A ratio representing the harmonic mean of recall and precision. The F1-score is used as a measure of quality for classification algorithms and information retrieval strategies, where 1 represents the best precision and recall and 0 represents the worst precision and recall. A harmonic mean of a set of quantities is the reciprocal of the arithmetic mean of the reciprocals of each quantity. The F score is thus calculated as 1 / (the arithmetic mean of the reciprocals), or: F = 1 / ( ( (1/recall) + (1/precision) ) / 2 ) F = 2*( (precision*recall) / (precision+recall) ) Recall is sensitivity STATO:0000233 Precision (PPV) is STATO:0000416 F1-score Harold Lehmann, Kenneth Wilkins, Muhammad Afzal, Joanne Dehnbostel, Brian S. Alper, Philippe Rocca-Serra F score F1 measure F-score term request: https://github.com/ISA-tools/stato/issues/93 https://pubmed.ncbi.nlm.nih.gov/35508113/ F-measure Expert Working Group Agreement: 2022-10-19 vote 6-0 by Joanne Dehnbostel, Muhammad Afzal, Jesus Lopez-Alcalde, Mario Tristan, Eric Harvey, Harold Lehmann sklearn.metrics.f1_score(y_true, y_pred, *, labels=None, pos_label=1, average='binary', sample_weight=None, zero_division='warn') source: https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html F-beta score ready for release