Sampling Bias Mitigation
Sampling Bias Mitigation is a methodological strategy in data collection that systematically adjusts for distortions arising from non-representative sampling to ensure that the resulting data accurately reflect the target population.
220
Publications
19.4K
Citations
915
Authors
354
Institutions
Publications per year
2017–2026
87
Parents
220
Yoan Fourcade, Jan O. Engler, Dennis Rödder et al. · PLoS ONE · 2014 · 1.1K citations · Full text
SMOTE for high-dimensional class-imbalanced data
Rok Blagus, Lara Lusa · BMC Bioinformatics · 2013 · 1.1K citations · Full text
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354

Cornell University
Ithaca, United States
6 h-index
10 publications
2.7K citations

Australian National University
Canberra, Australia
4 h-index
6 publications
613 citations
University of Washington
Seattle, United States
4 h-index
9 publications
805 citations
University of Oxford
Oxford, United Kingdom
4 h-index
5 publications
871 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
4 publications
279 citations
University of Cambridge
Cambridge, United Kingdom
4 h-index
5 publications
1.5K citations
University of Michigan
Ann Arbor, United States
4 h-index
5 publications
349 citations
University of California, Davis
Davis, United States
3 h-index
3 publications
358 citations
1–8 of 354
9 publications · 550 citations
9
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8 publications · 2.1K citations
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Repository · 6 publications · 164 citations
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Repository · 5 publications · 221 citations
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4 publications · 924 citations
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