Skip to content

DOC improve wording of the F1 score as a harmonic mean #21390

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 21, 2021
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion sklearn/metrics/_classification.py
Original file line number Diff line number Diff line change
Expand Up @@ -991,7 +991,7 @@ def f1_score(
):
"""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
The F1 score can be interpreted as a harmonic mean of the precision and
recall, where an F1 score reaches its best value at 1 and worst score at 0.
The relative contribution of precision and recall to the F1 score are
equal. The formula for the F1 score is::
Expand Down