Ch 11: Measuring Peformance in Classification Methods
- Kohen's kappa
- ROC curve
- List plot
False positives/negatives
| Observed | ||
| Predicted | Event | Nonevent |
| Event | TP | FP |
| Nonevent | FN | TN |
- False positive = Type I error:
- incorrect rejection of a true null hypothesis
- False negative = Type II error:
- incorrect acceptance of a false null hypothesis
- Sensitivity = true positive rate (TPR):
- TPR = TP/P = TP/(TP+FN)
- Specificity (SPC) = true negative rate:
- SPC = TN/N = TN/(TN+FP)
- Fallout = false positive rate (FPR):
- FPR = FP/N = FP/(TN+FP) = 1-SPC
