Multimodal Sleep Stage Detection On Sleep Edf
Métriques
Accuracy
Cohen's kappa
Macro-F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Cohen's kappa | Macro-F1 | Paper Title | Repository |
---|---|---|---|---|---|
Linear model | 85.7% | 0.806 | 0.809 | Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring | |
Scratch SeqSleepNet+ (EEG+EOG) | 82.2% | - | - | Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning | |
CatBoost | 86.4% | 0.812 | 0.802 | Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring |
0 of 3 row(s) selected.