Sensitivity (true positive rate)
Definition
The proportion of true matches correctly identified as matches. Sensitivity = TP / (TP + FN) = 1 minus FNR. A method with high sensitivity rarely misses a true match.
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 negative rate (FNR)
- The proportion of true matches (or true positives) that a classification method fails to detect, declaring them as non-matches. Also called the...
- 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...
- Specificity (true negative rate)
- The proportion of true non-matches correctly identified as non-matches. Specificity = TN / (TN + FP) = 1 minus FPR. A method...
Explained in
- False Positive and False Negative Error RatesThe proportion of true matches correctly identified as matches. Sensitivity = TP / (TP + FN) = 1 minus FNR. A method with high sensitivity rarely misses a true...