Hey everyone, I've stumbled upon an inconsistency with the F1 score and I can't seem to get around it. I have two lists y_true = [0, 1, 2, 2, 2] and y_pred = [0, 0, 2, 2, 1]. sklearn tells me that the macro-averaged F1 score is 0.488888... If I understand correctly the macro-average F1 score is the harmonic mean of the macro-average precision score and the macro-average recall score. sklearn tells me that the macro-average precision is 0.5 whilst the macro-average recall is 0.555555... If use the statistics.harmonic_mean function from Python's standard library this gives me around 0.526315.
So which is correct: 0.488888 or 0.526315? I apologize in advance if I've overlooked something silly. Best regards. -- Max Halford +336 28 25 13 38
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