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
Parents
144
Measuring Socioeconomic Status
Paul T. Cirino, Christopher E. Chin, Rose A. Sevcik et al. · Assessment · 2002 · 364 citations
Consensus indices for comparing classifications
F. James Rohlf · Mathematical Biosciences · 1982 · 298 citations
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University of California, Santa Barbara, United States
2 publications · 106 citations
2
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2
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1–5 of 612
334
University College London
London, United Kingdom
4 h-index
5 publications
595 citations
Iowa State University
Ames, United States
4 h-index
8 publications
345 citations

University of British Columbia
Vancouver, Canada
3 h-index
4 publications
213 citations
University of Washington
Seattle, United States
3 h-index
8 publications
771 citations

Johns Hopkins University
Baltimore, United States
3 h-index
3 publications
269 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
6 publications
315 citations
University of California, Berkeley
Berkeley, United States
3 h-index
3 publications
127 citations

Deakin University
Burwood, Australia
3 h-index
3 publications
93 citations
1–8 of 334
6 publications · 586 citations
6
h-index
Repository · 4 publications · 80 citations
4
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JPAH · 2 publications · 49 citations
2
h-index
2 publications · 178 citations
2
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2 publications · 37 citations
2
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