Ensemble Underfitting

Ensemble Underfitting is a machine learning phenomenon characterized by insufficient model complexity in ensemble methods, resulting in systematic failure to capture underlying patterns in the training data.

27

Publications

1.6K

Citations

79

Authors

38

Institutions

Publications per year

2017–2026

12

Authors

79

  1. XY
    Xin Yao

    University of Birmingham, United Kingdom

    2 publications · 173 citations

    2

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  2. NL
    Nitin Liladhar Rane

    University of Mumbai, India

    2 publications · 115 citations

    2

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  3. PS
    Peter Sollich

    King's College London, United Kingdom

    2 publications · 481 citations

    2

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  4. AK
    Anders Krogh

    University of Copenhagen, Denmark

    2 publications · 481 citations

    2

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  5. JR
    Jayesh Rane

    University of Mumbai, India

    2 publications · 115 citations

    2

    h-index

1–5 of 79

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 61 citations

    2

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  2. Soft Computing

    1 publications · 22 citations

    1

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  3. SSRN Electronic Journal

    Repository · 1 publications · 24 citations

    1

    h-index

  4. 1

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  5. 1

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1–5