Credit Card Fraud Detection with Unbalanced Real and Synthetic dataset using Machine Learning models
Author:
Affiliation:
1. NIT Tiruchirappalli,Department of Computer Application,Tiruchirappalli,India
2. Rane Polytechnic,Department of Mechatronics Engineering,Tiruchirappalli,India
3. National Institute of Technology,Computer Applications,Tiruchirappalli,Tamil Nadu
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9783220/9783472/09783529.pdf?arnumber=9783529
Reference22 articles.
1. SCARFF : A scalable framework for streaming credit card fraud detection with spark
2. Calibrating Probability with Undersampling for Unbalanced Classification
3. Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization
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1. Automated Fraud Detection in Financial Transactions using Machine Learning: An Ensemble Perspective;2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA);2024-03-15
2. Credit Card Fraud Detection Methods: A Review;E3S Web of Conferences;2023
3. A Hybrid Machine Learning Approach for Credit Card Fraud Detection;International Journal of Information Technology Project Management;2022-11-04
4. Intelligent Identification of the Line-Transformer Relationship in Distribution Networks Based on GAN Processing Unbalanced Data;Sustainability;2022-07-14
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