Statistical quantification of confounding bias in machine learning models

BACKGROUND: The lack of nonparametric statistical tests for confounding bias significantly hampers the development of robust, valid, and generalizable predictive models in many fields of research. Here I propose the partial confounder test, which, for a given confounder variable, probes the null hyp...

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Detalles Bibliográficos
Autor principal: Spisak, Tamas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412867/
https://www.ncbi.nlm.nih.gov/pubmed/36017878
http://dx.doi.org/10.1093/gigascience/giac082

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412867/
https://www.ncbi.nlm.nih.gov/pubmed/36017878
http://dx.doi.org/10.1093/gigascience/giac082

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