Table 2.
Statistics on the diagnostic efficacy of different models in the training and validation groups.
| Model | Group | Sensitivity | Specificity | PPV | NPV | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| Logistic | Training | 0.800 | 0.622 | 0.721 | 0.718 | 0.720 | 0.759 |
| Test | 0.792 | 0.350 | 0.594 | 0.583 | 0.591 | 0.679 | |
|
| |||||||
| Decision tree | Training | 0.909 | 0.711 | 0.794 | 0.865 | 0.820 | 0.847 |
| Test | 0.917 | 0.400 | 0.647 | 0.800 | 0.682 | 0.759 | |
|
| |||||||
| Random forest | Training | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| Test | 0.875 | 0.550 | 0.700 | 0.786 | 0.727 | 0.778 | |
|
| |||||||
| SVM | Training | 0.909 | 0.622 | 0.746 | 0.848 | 0.780 | 0.820 |
| Test | 0.875 | 0.250 | 0.583 | 0.625 | 0.591 | 0.700 | |
|
| |||||||
| AdaBoost | Training | 0.782 | 0.867 | 0.878 | 0.765 | 0.820 | 0.827 |
| Test | 0.792 | 0.450 | 0.633 | 0.643 | 0.636 | 0.704 | |