Table 4.
Binary classification performance comparison of original features and GDCA-transformed features
| Task | Feature | Original Features | Transformed Features | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Classifier | F1 Score | Accuracy | Precision | Recall | F1 Score | Accuracy | Precision | Recall | |
| CN vs. EMCI | SVM | 72.73% | 66.04% | 64.86% | 82.76% | 78.69% | 75.47% | 75.00% | 82.76% |
| MLP | 75.41% | 71.70% | 71.88% | 79.31% | 78.57% | 77.36% | 81.48% | 75.86% | |
| GB | 75.41% | 71.70% | 71.88% | 79.31% | 77.19% | 75.47% | 78.57% | 75.86% | |
| GDA | 66.67% | 64.15% | 67.86% | 65.52% | 80.70% | 79.25% | 82.14% | 79.31% | |
| EMCI vs. LMCI | SVM | 54.05% | 64.58% | 55.56% | 52.63% | 65.00% | 70.83% | 61.90% | 68.42% |
| MLP | 59.46% | 68.75% | 61.11% | 57.89% | 72.73% | 75.00% | 64.00% | 84.21% | |
| GB | 48.48% | 64.58% | 57.14% | 42.11% | 60.00% | 75.00% | 81.82% | 47.37% | |
| GDA | 52.00% | 50.00% | 41.94% | 68.42% | 77.78% | 83.33% | 82.35% | 73.68% | |