A Comparative Analysis of Credit Card Detection Models
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-2850-7_18
Reference18 articles.
1. R. Almutairi, A. Godavarthi, A.R. Kotha, E. Ceesay, in Analyzing Credit Card Fraud Detection Based on Machine Learning Models. 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS) (IEEE, 2022), pp. 1–8
2. B. Al-Smadi, M. Min, in A Critical Review of Credit Card Fraud Detection Techniques. 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), pp. 732–736 (2020)
3. A.H. Azizan, S.A. Mostafa, A. Mustapha, C.F.M. Foozy, M.H.A. Wahab, M.A. Mohammed, B.A. Khalaf, A machine learning approach for improving the performance of network intrusion detection systems. Ann. Emerg. Technol. Comput. (AETiC) 5(5), 201–208 (2021)
4. S. Bahramirad, A. Mustapha, M. Eshraghi, in Classification of Liver Disease Diagnosis: A Comparative Study. 2013 Second International Conference on Informatics & Applications (ICIA), pp. 42–46 (2013)
5. L. Borah, B. Saleena, B. Prakash, Credit card fraud detection using data mining techniques. J. Seybold Rep. 15(9) (2020)
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