Investigating Credit Card Payment Fraud with Detection Methods Using Advanced Machine Learning
Victor Chang,
Basit Ali,
Lewis Golightly
et al.
Abstract:In the cybersecurity industry, where legitimate transactions far outnumber fraudulent ones, detecting fraud is of paramount significance. In order to evaluate the accuracy of detecting fraudulent transactions in imbalanced real datasets, this study compares the efficacy of two approaches, random under-sampling and oversampling, using the synthetic minority over-sampling technique (SMOTE). Random under-sampling aims for fairness by excluding examples from the majority class, but this compromises precision in fa… Show more
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