Table 2.
The evaluation metrics of three classes averaged with our customized CNN model.
| Model | Evaluation Metrics | |||||
|---|---|---|---|---|---|---|
| Customized CNN Techniques | Accuracy | Precision | Sensitivity | Specificity | F1-Score | AUC |
| Adam Optimizer LR = 0.001 25% | 97.1% | 96.3% | 96.3% | 97.0% | 96.3% | 0.990 |
| Adam Optimizer LR = 0.001 30% | 97.0% | 97.0% | 92.6% | 96.9% | 94.3% | 0.983 |
| Adam Optimizer LR = 0.0001 25% | 96.3% | 95.0% | 96.0% | 96.9% | 95.6% | 0.970 |
| Adam Optimizer LR = 0.0001 30% | 95.1% | 92.0% | 93.6% | 95.5% | 92.6% | 0.976 |
| RMSprop Optimizer LR = 0.001 25% | 98.6% | 98.0% | 98.0% | 98.5% | 98.0% | 0.976 |
| RMSprop Optimizer LR = 0.001 30% | 94.0% | 90.6% | 87.6% | 93.8% | 89.3% | 0.953 |
| RMSprop Optimizer LR = 0.0001 25% | 94.6% | 92.0% | 95.3% | 96.0% | 93.6% | 0.976 |
| RMSprop Optimizer LR = 0.0001 30% | 91.8% | 87.3% | 91.3% | 93.6% | 89.3% | 0.966 |