One-versus-rest Classification

One-Versus-Rest Classification is a multi-class classification strategy that, as a singular method, generalizes binary classifiers to multi-class settings by training one classifier per class to distinguish that class from all others collectively.

55

Publications

3.1K

Citations

172

Authors

90

Institutions

Publications per year

2017–2026

23

Variants

One-against-all ClassificationOne-versus-all ClassificationOva ClassificationOvr Classification

Authors

172

  1. JA
    Jayadeva

    Indian Institute of Technology Delhi, India

    2 publications · 154 citations

    2

    h-index

  2. JX
    Jianhua Xuan

    Virginia Tech, United States

    2 publications · 39 citations

    2

    h-index

  3. FS
    Fahad Shahbaz Khan

    Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates

    2 publications · 441 citations

    2

    h-index

  4. DK
    Dinesh Kumar

    RMIT University, Australia

    2 publications · 154 citations

    2

    h-index

  5. GY
    Guoqiang Yu

    University of Kentucky, United States

    2 publications · 39 citations

    2

    h-index

1–5 of 172

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 80 citations

    3

    h-index

  2. Neurocomputing

    2 publications · 175 citations

    2

    h-index

  3. Cyborg and Bionic Systems

    1 publications · 41 citations

    1

    h-index

  4. IEEE Transactions on Fuzzy Systems

    TFS · 1 publications · 85 citations

    1

    h-index

  5. IEEE Transactions on Smart Grid

    1 publications · 112 citations

    1

    h-index

1–5