Table 1. Confusion matrix for a binary classifier.
Predicted | |||
---|---|---|---|
Positive | Negative | ||
Positive | TP | FN | Sensitivity = TP/TP+FN |
Negative | FP | TN | Specificity = TN/TN+FP |
TP = True positive: Diseased individuals correctly diagnosed as sick; FP = False positive: Healthy individuals wrongly predicted as sick; TN = True negative: Healthy individuals correctly predicted as healthy; FN = False negative: Diseased individuals wrongly predicted as healthy.