Machine learning system | Sensitivity | Specificity | Overall accuracy | Balanced accuracy | Variance | PPV | AUROC |
---|
D_FF_Conic(6x12x12x12)a | 89.2 | 86.2 | 87.7 | 88.0 | 2.6 | 92.1 | 0.86 |
D_FF_Conic(4x12x12x12)a | 87.5 | 84.6 | 86.0 | 86.5 | 3.4 | 91.0 | 0.84 |
D_FF_Sn(48)a | 88.3 | 83.2 | 85.8 | 86.4 | 4.3 | 90.4 | 0.85 |
D_FF_Bp(24) a | 88.3 | 77.6 | 83.0 | 84.3 | 6.0 | 87.1 | 0.81 |
RandomForestb | 90.0 | 58.0 | 74.0 | 78.1 | 3.2 | 78.9 | 0.83 |
Logisticb | 82.5 | 62.5 | 72.5 | 75.1 | 5.6 | 79.7 | 0.74 |
- Employed machine learning systems are listed in decreasing order of overall accuracy. The results are the average of five testing experiments. Overall accuracy Arithmetic average of sensitivity and specificity, Balanced accuracy Weighted average of sensitivity and specificity, PPV Positive Predictive Value, AUROC Area Under the Receiver Operator Curve. Sensitivity, Specificity, Overall accuracy, Balanced accuracy, Variance and PPV are all expressed as percentage.