Utilization of Encoding, Early Stopping, Hyper Parameter Tuning, and Machine Learning Models for Bank Fraud Detection-Reference-Cited by-同舟云学术

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Utilization of Encoding, Early Stopping, Hyper Parameter Tuning, and Machine Learning Models for Bank Fraud Detection

Published:2023-11-25 Issue: Volume: Page:321-327
ISSN:
Container-title:2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)
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Author:

Islam Md Aminul¹^ORCID,Nag Anindya²^ORCID,Chowdhury Saumik³^ORCID,Fahim SM Firoz Ahmed⁴,Ghosh Arjan²,Mumtaj Nahi⁵^ORCID

Affiliation:

1. School of Engineering Computing, and Mathematics Oxford Brookes University,Oxford,UK

2. Computer Science & Engineering Discipline Khulna University,Khulna,Bangladesh,9208

3. Jashore University of Science & Technology,Department of Computer Science & Engineering,Jashore,Bangladesh,7408

4. American International University Bangladesh,Department of Computer Science & Engineering,Dhaka,Bangladesh

5. BSRM School of Engineering, Electrical and Electronics BRAC University,Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10456368/10456369/10456503.pdf?arnumber=10456503

Reference33 articles.

1. An intelligent system for user behavior detection in Internet Banking

2. Fraud detection system: A survey

3. Evaluating the benefits of using proactive transformed-domain-based techniques in fraud detection tasks

4. A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection

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