Cross-Subject Emotion Prediction Regression on SEED-IV
0.0832MSEEEGDancer
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| EEGDancerMethodology=Deep Learning2026.06 | 0.0832 | 0.2036 | 0.5465 | |
| DDCMethodology=Deep Learning2026.06 | 0.102 | 0.248 | 0.4485 | |
| BiDANNMethodology=Deep Learning2026.06 | 0.1032 | 0.2492 | 0.4291 | |
| RidgeMethodology=Traditional Machine Learning2026.06 | 0.1036 | 0.256 | 0.4316 | |
| DCORALMethodology=Deep Learning2026.06 | 0.1046 | 0.2516 | 0.441 | |
| DANNMethodology=Deep Learning2026.06 | 0.1054 | 0.2534 | 0.4089 | |
| LassoMethodology=Traditional Machine Learning2026.06 | 0.1064 | 0.2587 | 0.4511 | |
| EEGNetMethodology=Deep Learning2026.06 | 0.1067 | 0.2568 | 0.4408 | |
| DANMethodology=Deep Learning2026.06 | 0.1075 | 0.2558 | 0.3857 | |
| MLPMethodology=Traditional Machine Learning2026.06 | 0.1081 | 0.258 | 0.4697 | |
| Random ForestMethodology=Traditional Machine Learning2026.06 | 0.1086 | 0.2658 | 0.267 | |
| RGNNMethodology=Deep Learning2026.06 | 0.1154 | 0.2741 | 0.3442 | |
| GradientBoostingRegressorMethodology=Traditional Machine Learning2026.06 | 0.1199 | 0.2756 | 0.2505 | |
| Bayesian RidgeMethodology=Traditional Machine Learning2026.06 | 0.1532 | 0.3048 | 0.2932 | |
| SVRMethodology=Traditional Machine Learning2026.06 | 0.1623 | 0.3238 | 0.3771 | |
| HuberRegressorMethodology=Traditional Machine Learning2026.06 | 0.1713 | 0.3327 | 0.3291 | |
| Decision TreeMethodology=Traditional Machine Learning2026.06 | 0.1882 | 0.3454 | 0.1538 | |
| KNNMethodology=Traditional Machine Learning2026.06 | 0.1918 | 0.342 | 0.261 |