Classification on Liver ultrasound dataset (10% train, 90% test)
78.5AccuracyARMA-C3
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| ARMA-C3Loss Function=–, lambda_con=0.0012026.05 | 78.5 | 81.8 | 86.6 | 84.1 | |
| ARMALoss Function=MERIT + Cut, lambda_con=0.0012026.05 | 77.1 | 80.6 | 85.7 | 84 | |
| ARMALoss Function=DGI [27] + Mod, lambda_con=0.012026.05 | 74.5 | 82.4 | 80.1 | 81.1 | |
| SVCLoss Function=–, lambda_con=–2026.05 | 74.2 | 76.7 | 89.7 | 82.6 | |
| ARMALoss Function=Mod [29], lambda_con=–2026.05 | 74.2 | 79.1 | 85.1 | 81.8 | |
| APPNPLoss Function=–, lambda_con=–2026.05 | 73.7 | 78.4 | 85.2 | 81.6 | |
| ARMALoss Function=Baseline, lambda_con=–2026.05 | 73.7 | 79.2 | 83.7 | 81.3 | |
| Random ForestLoss Function=–, lambda_con=–2026.05 | 73.5 | 75.1 | 92.1 | 82.7 | |
| ARMALoss Function=Cut [48], lambda_con=–2026.05 | 73.4 | 78.9 | 83.7 | 81.1 | |
| GATLoss Function=MERIT[11] + Mod, lambda_con=0.012026.05 | 73.4 | 81.6 | 79.4 | 80.3 | |
| MLPClassifierLoss Function=–, lambda_con=–2026.05 | 73 | 81.7 | 78.2 | 79.9 | |
| ARMALoss Function=DGI + Cut, lambda_con=0.012026.05 | 72.9 | 84.1 | 74.9 | 79 | |
| JacobiConvLoss Function=–, lambda_con=–2026.05 | 72.6 | 79.6 | 81.3 | 80 | |
| GATLoss Function=MERIT + Cut, lambda_con=0.012026.05 | 72.6 | 80.7 | 79 | 79.6 | |
| XGBoostLoss Function=–, lambda_con=–2026.05 | 71.5 | 76 | 85.5 | 80.4 | |
| GATLoss Function=DGI + Mod, lambda_con=0.52026.05 | 71.2 | 84.7 | 69.3 | 76 | |
| GATLoss Function=Cut, lambda_con=–2026.05 | 71 | 80.8 | 76.1 | 78.1 | |
| GATLoss Function=DGI + Cut, lambda_con=0.0012026.05 | 70.8 | 82 | 70.4 | 75.2 | |
| GATLoss Function=Baseline, lambda_con=–2026.05 | 70.4 | 78.3 | 78.8 | 78.4 | |
| GATLoss Function=Mod, lambda_con=–2026.05 | 70.2 | 78.1 | 76.7 | 77.3 | |
| ARMA-C3Loss Function=N/A, lambda_con=0.0012026.05 | 0.785 | 0.818 | 0.866 | 0.841 | |
| ARMALoss Function=MERIT + Cut, lambda_con=0.0012026.05 | 0.771 | 0.806 | 0.857 | 0.84 | |
| ARMALoss Function=DGI + Mod, lambda_con=0.012026.05 | 0.745 | 0.824 | 0.801 | 0.811 | |
| SVCLoss Function=N/A, lambda_con=N/A2026.05 | 0.742 | 0.767 | 0.897 | 0.826 | |
| ARMALoss Function=Mod, lambda_con=N/A2026.05 | 0.742 | 0.791 | 0.851 | 0.818 | |
| APPNPLoss Function=N/A, lambda_con=N/A2026.05 | 0.737 | 0.784 | 0.852 | 0.816 | |
| ARMALoss Function=Baseline, lambda_con=N/A2026.05 | 0.737 | 0.792 | 0.837 | 0.813 | |
| Random ForestLoss Function=N/A, lambda_con=N/A2026.05 | 0.735 | 0.751 | 0.921 | 0.827 | |
| ARMALoss Function=Cut, lambda_con=N/A2026.05 | 0.734 | 0.789 | 0.837 | 0.811 | |
| GATLoss Function=MERIT + Mod, lambda_con=0.012026.05 | 0.734 | 0.816 | 0.794 | 0.803 | |
| MLPClassifierLoss Function=N/A, lambda_con=N/A2026.05 | 0.73 | 0.817 | 0.782 | 0.799 | |
| ARMALoss Function=DGI + Cut, lambda_con=0.012026.05 | 0.729 | 0.841 | 0.749 | 0.79 | |
| JacobiConvLoss Function=N/A, lambda_con=N/A2026.05 | 0.726 | 0.796 | 0.813 | 0.8 | |
| GATLoss Function=MERIT + Cut, lambda_con=0.012026.05 | 0.726 | 0.807 | 0.79 | 0.796 | |
| XGBoostLoss Function=N/A, lambda_con=N/A2026.05 | 0.715 | 0.76 | 0.855 | 0.804 | |
| GATLoss Function=DGI + Mod, lambda_con=0.52026.05 | 0.712 | 0.847 | 0.693 | 0.76 | |
| GATLoss Function=Cut, lambda_con=N/A2026.05 | 0.71 | 0.808 | 0.761 | 0.781 | |
| GATLoss Function=DGI + Cut, lambda_con=0.0012026.05 | 0.708 | 0.82 | 0.704 | 0.752 | |
| GATLoss Function=Baseline, lambda_con=N/A2026.05 | 0.704 | 0.783 | 0.788 | 0.784 | |
| GATLoss Function=Mod, lambda_con=N/A2026.05 | 0.702 | 0.781 | 0.767 | 0.773 |