Models | ROC(95%CI) | Cutoff | TP | TN | FP | FN | Sen | Spec | Acc | PPV | NPV | F1-score |
|---|
GLM | 0.87(0.80–0.94) | 0.069 | 18 | 443 | 69 | 4 | 0.82 | 0.87 | 0.86 | 0.21 | 0.99 | 0.33 |
RFM | 0.88(0.82–0.93) | 0.023 | 19 | 379 | 133 | 3 | 0.86 | 0.74 | 0.75 | 0.13 | 0.99 | 0.22 |
- Sen sensitivity, Spec specificity, TN true negative, FN false negative, TP true positive, FP false positive, PPV positive predict value, NPV negative predict value
- Sens(Recall) = TP/(TP + FN)
- Spec = TN/(TN + FP)
- PPV (Precision) = TP/(TP + FP)
- Acc=(TP + TN)/(TP + FP + TN + FN)
- F1-score = 2*(Precision*Recall)/(Precision + Recall)
