False Negative Rate (FNR)
Definition
The proportion of true matches (or true positives) that a classification method fails to detect, declaring them as non-matches. Also called the type II error rate, miss rate, or 1 minus sensitivity. FNR = FN / (FN + TP).
- Also called
- Type II error rate, miss rate
- Formula
- FNR = FN / (FN + TP)
- Related metric
- Sensitivity = 1 minus FNR
- Applies to
- Any binary classification method, not biometrics alone
Common questions
How does FNR relate to FMR/FNMR used in biometrics?+
FNR is the general statistical term for a missed true positive; FNMR is the biometrics-specific name for the same concept applied to matching. Outside biometrics, FNR covers any classifier, such as a presumptive drug test or a screening assay.
Why can a low FNR still be misleading?+
FNR alone says nothing about the false positive side or about class balance. A test tuned to near-zero FNR often does so by raising its false positive rate, so reporting FNR without FPR or the decision threshold hides the real tradeoff a lab is making.
Related terms
- Decision Threshold
- The cut-off score above which a classification method declares a positive result. Raising the threshold reduces FPR but increases FNR; lowering it...
- False Positive Rate (FPR)
- The proportion of true non-matches (or true negatives) that a classification method declares as matches (or positives). Also called the type I...
- ROC Curve
- Receiver operating characteristic curve: a plot of sensitivity (y-axis) against FPR (x-axis) as the decision threshold is swept from its most lenient...
- Sensitivity (True Positive Rate)
- The proportion of true matches correctly identified as matches. Sensitivity = TP / (TP + FN) = 1 minus FNR. A method...
- Specificity (True Negative Rate)
- The proportion of true non-matches correctly identified as non-matches. Specificity = TN / (TN + FP) = 1 minus FPR. A method...