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This research paper discusses the development of an efficient credit card fraud detection system using various machine learning algorithms, including Random Forest, Logistic Regression, and K-nearest neighbors. The study found that the Random Forest algorithm achieved the highest accuracy of 99.95% in detecting fraudulent transactions. The findings suggest that machine learning can significantly enhance fraud detection systems in financial institutions and payment processing companies.

Author

Victor Og

Language

EN