Table 2.
Test evaluation of two-class classifiers
| Model/Metric | Precision | Recall | F1-Score | Sensitivity | Specificity | Accuracy (%) |
|---|---|---|---|---|---|---|
| VGG16 | 0.945 | 0.969 | 0.952 | 0.969 | 0.933 | 95.12 |
| ResNet152V2 | 0.939 | 0.953 | 0.946 | 0.953 | 0.938 | 94.61 |
| InceptionresNetV2 | 0.924 | 0.938 | 0.931 | 0.938 | 0.923 | 93.07 |
| DenseNet201 | 0.901 | 0.989 | 0.943 | 0.989 | 0.892 | 94.10 |
| Proposed ensemble | 0.959 | 0.964 | 0.961 | 0.964 | 0.958 | 96.15 |
Final precision, recall, F1-score, sensitivity, specificity and accuracy of the proposed ensemble model for binary classification are highlighted in bold