diff --git a/0.23/modules/generated/sklearn.metrics.f1_score.html b/0.23/modules/generated/sklearn.metrics.f1_score.html index c9b7e9a434eb1..56523dd576376 100644 --- a/0.23/modules/generated/sklearn.metrics.f1_score.html +++ b/0.23/modules/generated/sklearn.metrics.f1_score.html @@ -169,7 +169,7 @@

sklearn.metrics.f1_score

-sklearn.metrics.f1_score(y_true, y_pred, *, labels=None, pos_label=1, average='binary', sample_weight=None, zero_division='warn')[source]
+sklearn.metrics.f1_score(y_true, y_pred, *, labels=None, pos_label=1, average='binary', sample_weight=None, zero_division='warn')[source]

Compute the F1 score, also known as balanced F-score or F-measure

The F1 score can be interpreted as a weighted average of the precision and recall, where an F1 score reaches its best value at 1 and worst score at 0. @@ -454,4 +454,4 @@

Examples using - \ No newline at end of file +