robROSE: A robust approach for dealing with imbalanced data in fraud detection
Crossref DOI link: https://doi.org/10.1007/s10260-021-00573-7
Published Online: 2021-06-07
Published Print: 2021-09
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Baesens, Bart
Höppner, Sebastiaan
Ortner, Irene
Verdonck, Tim http://orcid.org/0000-0003-1105-2028
Funding for this research was provided by:
BNP Paribas Fortis (Research Chair in Fraud Analytics)
Onderzoeksraad, KU Leuven (C16/15/068)
Text and Data Mining valid from 2021-06-07
Version of Record valid from 2021-06-07
Article History
Accepted: 24 May 2021
First Online: 7 June 2021