Algorithm | AUC | f1 | Accuracy | Specificity | Sensitivity |
---|---|---|---|---|---|
Random forest | 0.93 (0.88–0.98) | 0.92 (0.87–0.98) | 0.93 (0.88–0.98) | 0.86 (0.79–0.93) | 1 |
Logistic regression | 0.79 (0.71–0.87) | 0.79 (0.71–0.87) | 0.79 (0.71–0.87) | 0.81 (0.73–0.89) | 0.77 (0.69–0.85) |
KNN | 0.81 (0.74–0.89) | 0.81 (0.73–0.89) | 0.81 (0.74–0.89) | 0.81 (0.73–0.89) | 0.82 (0.74–0.89) |
SVM | 0.52 (0.43–0.62) | 0.09 (0.03–0.15) | 0.54 (0.44–0.63) | 0.05 (0.01–0.09) | 1 |
Decision tree | 0.75 (0.66–0.83) | 0.78 (0.70–0.86) | 0.74 (0.66–0.83) | 0.95 (0.91–0.99) | 0.55 (0.45–0.64) |