Machine Learning Classification Based Techniques for Fraud Discovery in Credit Card Datasets-Reference-Cited by-同舟云学术

Machine Learning Classification Based Techniques for Fraud Discovery in Credit Card Datasets

Published:2021 Issue: Volume: Page:26-38
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Ogundokun Roseline Oluwaseun,Misra Sanjay^ORCID,Ogundokun Opeyemi Eyitayo,Oluranti Jonathan,Maskeliunas Rytis

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-89654-6_3

Reference47 articles.

1. Tingfei, H., Guangquan, C., Kuihua, H.: Using variational autoencoding in credit card fraud detection. IEEE Access 8, 149841–149853 (2020)

2. Salazar, A., Safont, G., Vergara, L.: Semi-supervised learning for imbalanced classification of credit card transactions. In: 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1–7. IEEE (July 2018)

3. Gao, J., Zhou, Z., Ai, J., Xia, B., Coggeshall, S.: Predicting credit card transaction fraud using machine learning algorithms. J. Intell. Learn. Syst. Appl. 11(3), 33–63 (2019)

4. Yee, O.S., Sagadevan, S., Malim, N.: Credit card fraud detection using machine learning as a data mining technique. J. Telecommun. Electron. Comput. Eng. (JTEC) 10(1–4), 23–27 (2018)

5. Roy, A., et al.: Deep learning detecting fraud in credit card transactions. In: 2018 Systems and Information Engineering Design Symposium (SIEDS), pp. 129–134. IEEE (April 2018)

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