Table 1.
Comparison and performance evaluation of the different proposed deep stacked sparse autoencoder neural network.
| Model number | Training accuracy | Test accuracy | Precision | F Score | Recall | AUC |
|---|---|---|---|---|---|---|
| SVM | – | – | 67.7% | 77.5% | 90.8% | – |
| Decision Tree | – | – | 58.7% | 63.8% | 70% | – |
| K-NN | – | – | 70.9% | 48.3% | 36.7% | – |
| 100 20 | 86.0% | 69.1% | 84.0% | 85.9% | 87.9% | 0.9145 |
| 100 40 | 98.1% | 89.1% | 99.4% | 99.4% | 99.4% | 0.9910 |
| 100 60 | 85.7% | 83.6% | 92.3% | 88.3% | 84.7% | 0.9230 |
| 100 80 | 92.2% | 76.4% | 92.9% | 94.76% | 96.7% | 0.9764 |
| 100 100 | 90.3% | 87.3% | 98.1% | 96.8% | 95.6% | 0.9777 |
| Chen et al.1 | – | – | 94.1% | 89.9% | 91.95^ | – |