FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes

With the increased use of machine learning algorithms to make decisions which impact people's lives, it is of extreme importance to ensure that predictions do not prejudice subgroups of the population with respect to sensitive attributes such as race or gender. Discrimination occurs when the pr...

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Detalhes bibliográficos
Autor principal: Salazar, Teresa (author)
Outros Autores: Santos, Miriam Seoane (author), Araújo, Helder (author), Abreu, Pedro Manuel Henriques da Cunha (author)
Formato: article
Idioma:eng
Publicado em: 2021
Assuntos:
Classification bias
fairness
imbalanced data
K-nearest neighborhood
oversampling
Texto completo:http://hdl.handle.net/10316/101209
País:Portugal
Oai:oai:estudogeral.sib.uc.pt:10316/101209

Texto Completo

http://hdl.handle.net/10316/101209

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