Weighted binary ELM optimized by the reptile search algorithm, application to credit card fraud detection
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-19508-x.pdf
Reference49 articles.
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2. Al-Shabi MA (2019) Credit card fraud detection using autoencoder model in unbalanced datasets. J Adv Math Comput Sci, 1–16. https://doi.org/10.9734/jamcs/2019/v33i530192
3. Almuteer AH, Aloufi AA, Alrashidi WO, Alshobaili JF, Ibrahim DM (2021) Detecting credit card fraud using machine learning. Int J Interact Mobile Technol 15(24):108–122. https://doi.org/10.3991/IJIM.V15I24.27355
4. Huang G-B, Siew C-K (2004) Extreme learning machine: RBF Network Case. ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. https://doi.org/10.1109/Icarcv.2004.1468985
5. Berahmand K, Daneshfar F, Sadat E, Yuefeng S (2024) Autoencoders and their applications in machine learning : a survey. Springer, Netherlands, in artificial intelligence review. https://doi.org/10.1007/s10462-023-10662-6
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