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 @@