Credit Card Fraud Payments Detection Using Machine Learning Classifiers on Imbalanced Data Set Optimized by Feature Selection-Reference-Cited by-同舟云学术

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Credit Card Fraud Payments Detection Using Machine Learning Classifiers on Imbalanced Data Set Optimized by Feature Selection

Published:2023 Issue: Volume: Page:233-250
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
Short-container-title:

Author:

Husejinović Admel^ORCID,Kevrić Jasmin^ORCID,Durmić Nermina^ORCID,Jukić Samed^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43056-5_19

Reference57 articles.

1. Nilson Report: News and Statistics for Card and Mobile Payment Executives (2021). https://nilsonreport.com/. Accessed 30 Apr 2022

2. Identity Theft Reports | Tableau Public (2021). https://public.tableau.com/app/profile/federal.trade.commission/viz/IdentityTheftReports/TheftTypesOverTime. Accessed 20 Apr 2022

3. E. Central Bank: Seventh report on card fraud (2021)

4. Shimpi, P.R.: Survey on credit card fraud detection techniques. Int. J. Eng. Comput. Sci. (2016)

5. Ndueso John, S., et al.: Realtime fraud detection in the banking sector using data mining techniques/algorithm electronic customer relationship management system-e-products and identity fraud view project reliability of electric power systems view project realtime fraud detection (2016)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Credit Card Fraud Detection Using Tree-Based Algorithms For Highly Imbalanced Data;2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI);2024-04-13

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