Discriminative machine learning for maximal representative subsampling

Biased population samples pose a prevalent problem in the social sciences. Therefore, we present two novel methods that are based on positive-unlabeled learning to mitigate bias. Both methods leverage auxiliary information from a representative data set and train machine learning classifiers to dete...

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Detalles Bibliográficos
Autores principales: Hauptmann, Tony, Fellenz, Sophie, Nathan, Laksan, Tüscher, Oliver, Kramer, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684887/
https://www.ncbi.nlm.nih.gov/pubmed/38017053
http://dx.doi.org/10.1038/s41598-023-48177-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684887/
https://www.ncbi.nlm.nih.gov/pubmed/38017053
http://dx.doi.org/10.1038/s41598-023-48177-3

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