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Credit Card Fraud Detection with ML Techniques by Bolaji Odegbesan is a document available to read on EtoBox.

What is Credit Card Fraud Detection with ML Techniques about?

The document discusses a study on credit card fraud detection using various machine learning algorithms to address the challenges posed by imbalanced datasets. It evaluates nine algorithms, including Random Forest and k-nearest neighbors, alongside three sampling techniques to improve detection accuracy, with Random Forest achieving the highest accuracy rate of 99.96%. The study highlights the increasing prevalence of credit card fraud and the need for effective detection methods in the evolving digital pay

Author

Bolaji Odegbesan

Language

EN