The most often happening problem in the modern society is currently credit card fraud detection. This is a result of e-commerce systems and growing online transactions. Usually, credit card fraud occurs either when the card was stolen for any one of the illegal uses or even when the fraudster makes use of the credit card data. We are having many credit card issues in the current society. Introduced to identify the fraudulent activity was the credit card fraud detection system. This work intends to mostly concentrate on machine learning methods. The Adaboost algorithm and the random forest method are the applied ones. Accuracy, precision, recall, and F1-score define the outcomes of both methods. Plotting of the ROC curve depends on the confusion matrix. The best method used to identify the fraud is the Random Forest and Adaboost algorithms’ comparison reveals which one has the highest accuracy, precision, recall, and F1-score.
Credit Card Fraud Detection Using Machine Learning
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