Abstract
Abstract: The use of credit cards has become commonplace in our daily lives, transforming the way we make cashless payments and making all types of transactions more convenient for buyers. However, credit card fraud has also become increasingly prevalent as the number of users has risen. Criminals may illegally obtain an individual's credit card information and use it for fraudulent activities. This project involved collecting a sample of a publicly available dataset from Kaggle, consisting of 284,807 credit card transactions. Extreme Gradient Boost was used to detect fraudulent transactions, and it was found to be the most effective method, achieving the highest AUC value of 97.67% after thorough analysis.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
