Data & Analytics
(Spezifität)Specificity
Also known as:
True Negative Rate
TNR
Selectivity
Updated: 2/12/2026
The proportion of correctly classified negative cases out of all actual negative cases.
Quick Summary
Specificity = correctly identified negatives / all negatives – the counterpart to recall for the ROC curve.
Explanation
Specificity = TN / (TN + FP). Together with sensitivity it forms the ROC curve.
Marketing Relevance
High specificity reduces false positives – critical with expensive follow-up tests.
Common Pitfalls
Specificity alone ignores false negatives. Adapt trade-off with sensitivity.
Origin & History
Specificity comes from medical diagnostics and signal detection theory (1950s).
Comparisons & Differences
Specificity vs. Recall / Sensitivity
Sensitivity measures true positives; specificity measures true negatives.