Multimodal Sleep Stage Detection On Sleep Edf
评估指标
Accuracy
Cohen's kappa
Macro-F1
评测结果
各个模型在此基准测试上的表现结果
| Paper Title | Repository | ||||
|---|---|---|---|---|---|
| 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 | |
| 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 |
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