Method | Accuracy | Specificity | Precision | Recall | F1-score | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|---|---|---|
SAMME | 0.666 | 0.683 | 0.672 | 0.649 | 0.660 | 0.333 | 0.666 | 0.748 |
DT | 0.611 | 0.809 | 0.711 | 0.412 | 0.505 | 0.253 | 0.610 | 0.709 |
GPC | 0.707 | 0.604 | 0.692 | 0.811 | 0.738 | 0.433 | 0.707 | 0.799 |
KNN | 0.695 | 0.560 | 0.654 | 0.830 | 0.731 | 0.406 | 0.695 | 0.785 |
GNB | 0.654 | 0.645 | 0.651 | 0.662 | 0.656 | 0.308 | 0.654 | 0.741 |
QDA | 0.629 | 0.472 | 0.599 | 0.786 | 0.679 | 0.272 | 0.629 | 0.746 |
RF | 0.618 | 0.612 | 0.618 | 0.624 | 0.620 | 0.237 | 0.618 | 0.715 |
Linear-SVM | 0.692 | 0.673 | 0.685 | 0.712 | 0.698 | 0.386 | 0.692 | 0.771 |
RBF-SVM | 0.530 | 1.000 | 0.994 | 0.060 | 0.112 | 0.172 | 0.530 | 0.762 |
SNF-NN | 0.783 | 0.754 | 0.769 | 0.813 | 0.790 | 0.569 | 0.879 | 0.856 |