Emotion Prediction Regression on SEED (Cross-Subject)
0.0713MSEEEGDancer
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| EEGDancerMethod Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.0713 | 0.2012 | 0.7968 | |
| DDC*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1034 | 0.2469 | 0.6708 | |
| EEGNet*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1134 | 0.2499 | 0.6628 | |
| Ridge*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1201 | 0.2865 | 0.6367 | |
| DCORAL*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1201 | 0.2712 | 0.649 | |
| GradientBoostingRegressor*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1243 | 0.2832 | 0.6173 | |
| MLP*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1273 | 0.2742 | 0.6113 | |
| Lasso*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1281 | 0.2995 | 0.5868 | |
| DANN*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.132 | 0.2814 | 0.6634 | |
| RGNN*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1656 | 0.3388 | 0.337 | |
| KNN*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1749 | 0.3113 | 0.4459 | |
| DAN*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.177 | 0.3406 | 0.3648 | |
| BiDANN*Method Category=Deep Learning Method, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.1837 | 0.371 | 0.3737 | |
| Beysian Ridge*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.2502 | 0.3969 | 0.4494 | |
| SVR*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.2586 | 0.4033 | 0.4594 | |
| HuberRegressor*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.2613 | 0.4048 | 0.4591 | |
| Decision Tree*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.2721 | 0.3691 | 0.3042 | |
| Random Forest*Method Category=Traditional Machine Learning, Evaluation Protocol=Cross-Subject, Input Features=Differential Entropy (DE)2026.06 | 0.2721 | 0.3691 | 0.3042 |