From e5d787d4e5fba0f19c00fa274b2d3c689c0dd29b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Lucca=20Zen=C3=B3bio?= Date: Tue, 13 Aug 2019 10:59:39 -0300 Subject: [PATCH] Update _classification.py --- imblearn/metrics/_classification.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/imblearn/metrics/_classification.py b/imblearn/metrics/_classification.py index 9edbc9611..c728b5a9a 100644 --- a/imblearn/metrics/_classification.py +++ b/imblearn/metrics/_classification.py @@ -368,10 +368,9 @@ def specificity_score(y_true, sample_weight=None): """Compute the specificity - The specificity is the ratio ``tp / (tp + fn)`` where ``tp`` is the number - of true positives and ``fn`` the number of false negatives. The specificity - is intuitively the ability of the classifier to find all the positive - 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]. The best value is 1 and the worst value is 0.