Table 1 ROC results with KNN, SVM, XGBoost, RF, LR and DT classifiers of training set
Classifiers | Category | AUC | 95% CI | Sensitivity | Specificity |
|---|---|---|---|---|---|
KNN | NTM | 0.99 | 0.96–1.00 | 0.92 | 0.96 |
TB | 0.99 | 0.96–1.00 | 0.96 | 0.92 | |
SVM | NTM | 0.98 | 0.95–1.00 | 0.95 | 0.96 |
TB | 0.98 | 0.95–1.00 | 0.96 | 0.95 | |
XGBoost | NTM | 1.00 | 0.99–1.00 | 0.98 | 0.99 |
TB | 1.00 | 0.99–1.00 | 0.99 | 0.98 | |
RF | NTM | 1.00 | 0.99–1.00 | 0.99 | 1.00 |
TB | 1.00 | 0.99–1.00 | 1.00 | 0.99 | |
LR | NTM | 0.99 | 0.96–1.00 | 0.95 | 0.95 |
TB | 0.99 | 0.96–1.00 | 0.95 | 0.95 | |
DT | NTM | 1.00 | 1.00–1.00 | 1.00 | 1.00 |
TB | 1.00 | 1.00–1.00 | 1.00 | 1.00 |