Classification Agreement

Classification Agreement is a methodological construct in machine learning research that specifies the criteria and mechanisms by which multiple classifiers or human annotators achieve consistent categorical assignments for a given set of instances, thereby enabling reliable evaluation of model performance and data quality.

144

Publications

7.6K

Citations

612

Authors

334

Institutions

Publications per year

2017–2026

45

Authors

612

  1. GJ
    Gregory J. Welk

    Iowa State University, United States

    6 publications · 202 citations

    6

    h-index

  2. JA
    Jodee A. Schaben

    Iowa State University, United States

    3 publications · 76 citations

    3

    h-index

  3. YK
    Youngwon Kim

    MRC Epidemiology Unit, United Kingdom

    2 publications · 105 citations

    2

    h-index

  4. AM
    Amanda M. VanDerHeyden

    University of California, Santa Barbara, United States

    2 publications · 106 citations

    2

    h-index

  5. MP
    Massimo Poesio

    University of Essex, United Kingdom

    2 publications · 146 citations

    2

    h-index

1–5 of 612

Venues

  1. PLoS ONE

    6 publications · 586 citations

    6

    h-index

  2. PubMed

    Repository · 4 publications · 80 citations

    4

    h-index

  3. Journal of Physical Activity and Health

    JPAH · 2 publications · 49 citations

    2

    h-index

  4. Educational and Psychological Measurement

    2 publications · 178 citations

    2

    h-index

  5. International Journal of Remote Sensing

    2 publications · 37 citations

    2

    h-index

1–5