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Models/NB

NB

Reported on 26 benchmarks across 3 tasks

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

Methodology16 results

  • Multi-Label Text ClassificationonMVICTOR (theme)
    Average F1
    0.3797
    best: 0.8882 (XGBoost)
  • Multi-Label Text ClassificationonMVICTOR (theme)
    Weighted F1
    0.6062
    best: 0.9072 (XGBoost)
  • Multi-Label Text ClassificationonSVICTOR (theme)
    Average F1
    0.5121
    best: 0.8887 (XGBoost)
  • Multi-Label Text ClassificationonSVICTOR (theme)
    Weighted F1
    0.4875
    best: 0.8634 (XGBoost)
  • Multi-Label Text ClassificationonBVICTOR
    Average F1
    0.6335
    best: 0.8843 (XGBoost)
  • Multi-Label Text ClassificationonBVICTOR
    Weighted F1
    0.6955
    best: 0.8957 (XGBoost)
  • ClassificationonMVICTOR (type)
    Average F1
    0.4772
    best: 0.7505 (CNN + CRF)
  • ClassificationonMVICTOR (type)
    Weighted F1
    0.8477
    best: 0.9537 (CNN + CRF)
  • ClassificationonSVICTOR (type)
    Average F1
    0.5979
    best: 0.774 (CNN + CRF)
  • ClassificationonSVICTOR (type)
    Weighted F1
    0.8893
    best: 0.9533 (CNN + CRF)
  • ClassificationonMVICTOR (theme)
    Average F1
    0.3797
    best: 0.8882 (XGBoost)
  • ClassificationonMVICTOR (theme)
    Weighted F1
    0.6062
    best: 0.9072 (XGBoost)
  • ClassificationonSVICTOR (theme)
    Average F1
    0.5121
    best: 0.8887 (XGBoost)
  • ClassificationonSVICTOR (theme)
    Weighted F1
    0.4875
    best: 0.8634 (XGBoost)
  • ClassificationonBVICTOR
    Average F1
    0.6335
    best: 0.8843 (XGBoost)
  • ClassificationonBVICTOR
    Weighted F1
    0.6955
    best: 0.8957 (XGBoost)

Natural Language Processing10 results

  • Text ClassificationonMVICTOR (type)
    Average F1
    0.4772
    best: 0.7505 (CNN + CRF)
  • Text ClassificationonMVICTOR (type)
    Weighted F1
    0.8477
    best: 0.9537 (CNN + CRF)
  • Text ClassificationonSVICTOR (type)
    Average F1
    0.5979
    best: 0.774 (CNN + CRF)
  • Text ClassificationonSVICTOR (type)
    Weighted F1
    0.8893
    best: 0.9533 (CNN + CRF)
  • Text ClassificationonMVICTOR (theme)
    Average F1
    0.3797
    best: 0.8882 (XGBoost)
  • Text ClassificationonMVICTOR (theme)
    Weighted F1
    0.6062
    best: 0.9072 (XGBoost)
  • Text ClassificationonSVICTOR (theme)
    Average F1
    0.5121
    best: 0.8887 (XGBoost)
  • Text ClassificationonSVICTOR (theme)
    Weighted F1
    0.4875
    best: 0.8634 (XGBoost)
  • Text ClassificationonBVICTOR
    Average F1
    0.6335
    best: 0.8843 (XGBoost)
  • Text ClassificationonBVICTOR
    Weighted F1
    0.6955
    best: 0.8957 (XGBoost)