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Feature Based Selection Technique For Credit Card Fraud Detection System Using Machine Learning Algorithms

Olanlokun, Olaitan (2021) Feature Based Selection Technique For Credit Card Fraud Detection System Using Machine Learning Algorithms. Masters thesis, Dublin, National College of Ireland.

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One of the three most common forms of online fraud has been recognized as credit card fraud. Every year, these costs financial institutions billions of dollars. While the field of credit card fraud detection using machine learning algorithms has been extensively researched, numerous studies have revealed that there are still a considerable amount of false positives or false alarms. These false positives indicate people who may be denied access to products and/or services because their transactions are incorrectly classified as credit card fraud by the detection model, even though they are lawful. This ultimately leads to the objective of this proposed research. To compare and achieve the lowest possible false positive rate, the research proposes the use of different feature selection techniques such as recursive feature elimination and correlation-based feature selection, combined with machine learning algorithms such as random forest and logistic regression.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Credit card fraud; machine learning algorithms; feature selection techniques; false positive rate
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
H Social Sciences > HG Finance > Credit. Debt. Loans.
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Online Shopping
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Online Shopping
Divisions: School of Computing > Master of Science in Cyber Security
Depositing User: Clara Chan
Date Deposited: 01 Nov 2021 12:24
Last Modified: 01 Nov 2021 12:56

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