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Sep 5, 2019
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Update _classification.py #592

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7 changes: 3 additions & 4 deletions imblearn/metrics/_classification.py
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Expand Up @@ -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.

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