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eNauka >  Results >  Investigating Oversampling Techniques for Fair Machine Learning Models
Title: Investigating Oversampling Techniques for Fair Machine Learning Models
Authors: Rančić, Sanja  ; Radovanović, Sandro  ; Delibašić, Boris  
Issue Date: 2021
Publication: Lecture Notes in Business Information Processing
ISSN: 1865-1348 Lecture Notes in Business Information Processing (Germany) Search Idenfier
Publisher: Springer Science and Business Media Deutschland GmbH
Type: Conference Paper
Collation: vol. 414 LNBIP str. 110-123
DOI: 10.1007/978-3-030-73976-8_9
Scopus-ID: 2-s2.0-85111010796
URI: https://rfos.fon.bg.ac.rs/handle/123456789/2263
https://enauka.gov.rs/handle/123456789/169170
Project: This work was partially funded in part by the ONR/ONR Global under Grant N62909-19-1-2008. We would like to thank Saga New Frontier Group for supporting this research.
Metadata source: Migracija
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