Predictive Parity
Predictive Parity is a fairness metric in machine learning that requires the positive predictive value of a model to be equal across all protected groups, ensuring that the probability of a correct positive prediction is group-independent.
17
Publications
626
Citations
59
Authors
23
Institutions
Publications per year
2017–2026
13
17
Classification with Fairness Constraints
L. Elisa Celis, Lingxiao Huang, Vijay Keswani et al. · 2019 · 229 citations · Full text
Computing, Data Science, Data Mining +15
The physical size of gestating sows1
John J. McGlone, B. Vines, Anthony Rudine et al. · Journal of Animal Science · 2004 · 66 citations
Melissa Hamilton · Behavioral Sciences & the Law · 2019 · 52 citations · Full text
On the Moral Justification of Statistical Parity
Corinna Hertweck, Christoph Heitz, Michele Loi · 2021 · 46 citations · Full text
1–5 of 17
59
2
h-index
2
h-index
International Computer Science Institute, United States
2 publications · 32 citations
2
h-index
2
h-index
1
h-index
1–5 of 59
23
University of Zurich
Zurich, Switzerland
3 h-index
4 publications
129 citations
ZHAW Zurich University of Applied Sciences
Winterthur, Switzerland
2 h-index
4 publications
128 citations
Université de Montréal
Montreal, Canada
1 h-index
1 publications
13 citations

International Computer Science Institute
Berkeley, United States
1 h-index
1 publications
22 citations
Columbia University
New York, United States
1 h-index
2 publications
34 citations
Max Planck Institute for Software Systems
Saarbrücken, Germany
1 h-index
1 publications
19 citations

Harvard University Press
Cambridge, United States
1 h-index
1 publications
14 citations

University of British Columbia
Vancouver, Canada
1 h-index
4 publications
48 citations
1–8 of 23
Repository · 2 publications · 25 citations
2
h-index
1 publications · 12 citations
1
h-index
Repository · 1 publications · 27 citations
1
h-index
JAMIA · 1 publications · 17 citations
1
h-index
1 publications · 52 citations
1
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1–5