We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
There was an error while loading. Please reload this page.
1 parent 44ac642 commit 7cb004dCopy full SHA for 7cb004d
imblearn/metrics/_classification.py
@@ -368,10 +368,9 @@ def specificity_score(y_true,
368
sample_weight=None):
369
"""Compute the specificity
370
371
- The specificity is the ratio ``tp / (tp + fn)`` where ``tp`` is the number
372
- of true positives and ``fn`` the number of false negatives. The specificity
373
- is intuitively the ability of the classifier to find all the positive
374
- samples.
+ The specificity is the ratio ``tn / (tn + fp)`` where ``tn`` is the number
+ of true negatives and ``fn`` the number of false negatives. The specificity
+ quantifies the ability to avoid false positives_[1].
375
376
The best value is 1 and the worst value is 0.
377
0 commit comments