Combining unsupervised and supervised learning in credit card fraud detection-Reference-Cited by-同舟云学术

Combining unsupervised and supervised learning in credit card fraud detection

Published:2021-05 Issue: Volume:557 Page:317-331
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Carcillo Fabrizio,Le Borgne Yann-Aël,Caelen Olivier,Kessaci Yacine,Oblé Frédéric,Bontempi Gianluca

Funder

Innoviris

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference38 articles.

1. Example-dependent cost-sensitive decision trees;Bahnsen;Expert Syst. Appl.,2015

2. Feature engineering strategies for credit card fraud detection;Bahnsen;Expert Syst. Appl.,2016

3. Data mining for credit card fraud: a comparative study;Bhattacharyya;Decis. Support Syst.,2011

4. Analyzing bagging;Bühlmann;Ann. Stat.,2002

5. Random forests;Breiman;Mach. Learn.,2001

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