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Models/Linear model

Linear model

Reported on 12 benchmarks across 2 tasks · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical12 results

Sleep QualityonSleep-EDF-SC
Macro-F1· 2022-07-15
0.809
SOTA
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep QualityonSleep-EDF
Cohen's kappa· uses extra data· 2022-07-15
0.813
best: 0.82 (SleePyCo (Fpz-Cz only))
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep QualityonSleep-EDF
Macro-F1· uses extra data· 2022-07-15
0.805
best: 0.812 (SleePyCo (Fpz-Cz only))
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep QualityonSleep-EDF-SC
Cohen's kappa· 2022-07-15
0.806
best: 0.812 (CatBoost)
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep QualityonSleep-EDF-ST
Macro-F1· 2022-07-15
0.792
best: 0.795 (CatBoost)
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep QualityonSleep-EDF-ST
Cohen's kappa· 2022-07-15
0.759
best: 0.765 (CatBoost)
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep Stage DetectiononSleep-EDF
Cohen's kappa· uses extra data· 2022-07-15
0.813
best: 0.82 (SleePyCo (Fpz-Cz only))
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep Stage DetectiononSleep-EDF
Macro-F1· uses extra data· 2022-07-15
0.805
best: 0.812 (SleePyCo (Fpz-Cz only))
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring arXiv:2207.07753
Sleep QualityonMASS SS3
Cohen's kappa
0.786
best: 0.803 (CatBoost)
Sleep QualityonMASS SS3
Macro-F1
0.807
best: 0.817 (CatBoost)
Sleep Stage DetectiononMASS SS3
Cohen's kappa
0.786
best: 0.803 (CatBoost)
Sleep Stage DetectiononMASS SS3
Macro-F1
0.807
best: 0.817 (CatBoost)