Model | AUC (95% CI) | AUCPR (95% CI) | Sensitivity (95% CI) | Specificity (95% CI) | Balanced accuracy (95% CI) | F1 Score (95% CI) |
---|---|---|---|---|---|---|
LR | 0.90 (0.89–0.91) | 0.23 (0.20–0.26) | 0.81 (0.78–0.84) | 0.82 (0.82–0.83) | 0.82 (0.80–0.83) | 0.55 (0.54–0.56) |
Xgboost | 0.90 (0.89–0.91) | 0.23 (0.20–0.26) | 0.82 (0.79–0.85) | 0.81 (0.81–0.82) | 0.82 (0.80–0.83) | 0.55 (0.54–0.57) |
SVM | 0.90 (0.88–0.91) | 0.22 (0.20–0.25) | 0.81 (0.78–0.83) | 0.82 (0.81–0.82) | 0.81 (0.80–0.82) | 0.55 (0.54–0.57) |
NB | 0.80 (0.79–0.81) | 0.43 (0.42–0.46) | 0.91 (0.88–0.93) | 0.59 (0.59–0.60) | 0.75 (0.74–0.76) | 0.43 (0.42–0.43) |
Light-GBM | 0.87 (0.86–0.89) | 0.20 (0.18–0.24) | 0.55 (0.51–0.58) | 0.91 (0.91–0.92) | 0.73 (0.71–0.75) | 0.60 (0.59–0.61) |
RF | 0.79 (0.77–0.80) | 0.34 (0.32–0.36) | 0.75 (0.72–0.78) | 0.69 (0.69–0.7) | 0.72 (0.71–0.74) | 0.50 (0.50–0.50) |
MLP | 0.86 (0.85–0.87) | 0.19 (0.17–0.22) | 0.36 (0.33–0.39) | 0.96 (0.96–0.97) | 0.66 (0.66–0.68) | 0.63 (0.61–0.64) |
KNN | 0.75 (0.73–0.77) | 0.18 (0.16–0.20) | 0.14 (0.11–0.16) | 0.98 (0.98–0.99) | 0.56 (0.55–0.57) | 0.57 (0.56–0.58) |
DC | 0.51 (0.49–0.53) | 0.28 (0.26–0.30) | 0.52 (0.48–0.55) | 0.50 (0.50–0.51) | 0.51 (0.49–0.53) | 0.36 (0.36–0.36) |