Table 3.
Performance analysis of deep-learning and machine-learning model. Feature extracted from deep-learning proposed model and classify with machine-learning classifiers.
| Model | Accuracy | Precision | Recall | F1score |
|---|---|---|---|---|
| CoVIRNet Model with LR | 0.9279 | 0.9283 | 0.9264 | 0.9263 |
| CoVIRNet Model with MLP | 0.9446 | 0.9439 | 0.9437 | 0.9435 |
| CoVIRNet Model with GB | 0.9523 | 0.95141 | 0.9515 | 0.9512 |
| CoVIRNet Model with BT | 0.9613 | 0.9607 | 0.9607 | 0.9605 |
| CoVIRNet Model with RF | 0.9729 | 0.9774 | 0.9702 | 0.9732 |
LR, logistic regression; MLP, multilayer perceptron layer; GB, gradient boosting model; BT, bagging tree; RF, random forest.