Sleep Stage Detection On Mass Ss3
Metrics
Macro-F1
Macro-averaged Accuracy
Results
Performance results of various models on this benchmark
Model Name | Macro-F1 | Macro-averaged Accuracy | Paper Title | Repository |
|---|---|---|---|---|
| SPDTransNet | 0.8124 | 84.40% | Structure-Preserving Transformers for Sequences of SPD Matrices | |
| CatBoost | 0.817 | - | Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring | |
| Deep Sleep Net | - | - | Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging | |
| Simple Sleep Net | - | - | Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging | |
| Linear model | 0.807 | - | - | - |
| DeepSleepNet | 0.817 | - | DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG |
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