Abstract: Credit Card Fraud Detection Using Bagging and Boosting Algorithms
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Open Access | Fully Refereed | Peer Reviewed

ISSN: 2319-7064

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Student Project | Engineering Applications of Artificial Intelligence | India | Volume 10 Issue 7, July 2021

Credit Card Fraud Detection Using Bagging and Boosting Algorithms

Akansha Thakarke, Sakshi Ugale, Sneha Nale, Dr. Mrudul Dixit

The term Credit Card Fraud indicates that the defrauder is using your credit card credentials or has stolen your credit card for his/her financial benefit. Research tells us that due to economic expansion in recent years, credit card spending has increased. This eventually leads to increase in fraudulent credit card transactions. In the last few years, this has been a predominant issue; it causes a huge loss to the companies and the cardholder. The paper talks about machine learning techniques such as Logistic Regression, Na?ve Bayes, Boosting Classifier and Bagging classifier to detect credit card frauds.

Keywords: Bagging, Boosting, Credit Card fraud detection, Decision tree, Ensemble learning

Edition: Volume 10 Issue 7, July 2021

Pages: 849 - 852

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How to Cite this Article?

Akansha Thakarke, Sakshi Ugale, Sneha Nale, Dr. Mrudul Dixit, "Credit Card Fraud Detection Using Bagging and Boosting Algorithms", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SR21712231418, Volume 10 Issue 7, July 2021, 849 - 852

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