Model | Hamming loss | Accuracy | Precision | Recall | Macro-F1 |
ResNet [7] | 0.0555 | 0.6807 | 0.7393 | 0.6610 | 0.6850 |
xECGNet [7] | 0.0440 | 0.7304 | 0.8103 | 0.7313 | 0.7605 |
ML-GCN [7] | 0.0428 | 0.7177 | 0.8236 | 0.7085 | 0.7535 |
MLC-CNN [7] | 0.0472 | 0.6946 | 0.8034 | 0.6873 | 0.7337 |
P-GCN [7] | 0.0455 | 0.7016 | 0.8162 | 0.6970 | 0.7443 |
KGGR [7] | 0.0451 | 0.7132 | 0.8119 | 0.7062 | 0.7477 |
LCEGNet [7] | 0.0407 | 0.7500 | 0.8326 | 0.7375 | 0.7767 |
Ge et al. [8] | / | / | 0.830 | 0.827 | 0.828 |
Chen et al. [17] | / | / | / | / | 0.837 |
Ours | 0.0327 | 0.8139 | 0.8327 | 0.8508 | 0.8413 |