Table 1.
The evaluation metrics of three classes average with our standard CNN model.
| Model | Evaluation Metrics | |||||
|---|---|---|---|---|---|---|
| Standard CNN Techniques | Accuracy | Precision | Sensitivity | Specificity | F1-Score | AUC |
| Adam Optimizer LR = 0.001 25% | 94.2% | 91.6% | 95.3% | 95.9% | 93.0% | 0.970 |
| Adam Optimizer LR = 0.001 30% | 93.3% | 88.3% | 90.0% | 95.4% | 89.0% | 0.970 |
| Adam Optimizer LR = 0.0001 25% | 96.3% | 95.0% | 96.0% | 96.9% | 95.6% | 0.950 |
| Adam Optimizer LR = 0.0001 30% | 93.3% | 88.3% | 90.0% | 96.9% | 89.0% | 0.960 |
| RMSprop Optimizer LR = 0.001 25% | 94.2% | 89.3% | 95.3% | 95.4% | 92.3% | 0.966 |
| RMSprop Optimizer LR = 0.001 30% | 92.1% | 83.6% | 88.0% | 94.4% | 85.6% | 0.950 |
| RMSprop Optimizer LR = 0.0001 25% | 94.2% | 85.6% | 93.6% | 95.9% | 89.3% | 0.956 |
| RMSprop Optimizer LR = 0.0001 30% | 92.7% | 87.6% | 89.6% | 95.2% | 88.6% | 0.950 |