Table 4 The prediction results of different classifiers
Classifier | Accuracy (%) | Sensitivity (%) | Specificity (%) | MCC | AUC |
|---|---|---|---|---|---|
Logistic Regression | 78.60 | 77.50 | 78.76 | 0.4231 | 0.7286 |
K-Nearest Neighbor | 78.93 | 97.50 | 76.06 | 0.5295 | 0.8219 |
Decision Tree | 82.61 | 80.00 | 83.01 | 0.4927 | 0.8035 |
AdaBoost | 84.95 | 87.50 | 84.56 | 0.5658 | 0.7489 |
Support Vector Machine | 89.30 | 95.00 | 88.42 | 0.6774 | 0.8744 |
Random Forest | 94.65 | 92.50 | 94.98 | 0.7980 | 0.8956 |