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Models/CatBoost

CatBoost

Reported on 12 benchmarks across 2 tasks · 1 paper · 9 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
    Cohen's kappa· uses extra data· 2022-07-15
    0.816
    best: 0.82 (SleePyCo (Fpz-Cz only))
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonSleep-EDF
    Macro-F1· uses extra data· 2022-07-15
    0.81
    best: 0.812 (SleePyCo (Fpz-Cz only))
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonMASS SS3
    Cohen's kappa· 2022-07-15
    0.803
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonSleep-EDF-SC
    Cohen's kappa· 2022-07-15
    0.812
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonSleep-EDF-ST
    Macro-F1· 2022-07-15
    0.795
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonSleep-EDF-ST
    Cohen's kappa· 2022-07-15
    0.765
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep Stage DetectiononSleep-EDF
    Cohen's kappa· uses extra data· 2022-07-15
    0.816
    best: 0.82 (SleePyCo (Fpz-Cz only))
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep Stage DetectiononSleep-EDF
    Macro-F1· uses extra data· 2022-07-15
    0.81
    best: 0.812 (SleePyCo (Fpz-Cz only))
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep Stage DetectiononMASS SS3
    Cohen's kappa· 2022-07-15
    0.803
    SOTA
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonMASS SS3
    Macro-F1· 2022-07-15
    0.817
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep QualityonSleep-EDF-SC
    Macro-F1· 2022-07-15
    0.802
    best: 0.809 (Linear model)
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753
  • Sleep Stage DetectiononMASS SS3
    Macro-F1· 2022-07-15
    0.817
    Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringarXiv:2207.07753