Abstract
Abstract: Credit cards are frequently used in conjunction with the Internet to make payments. The project primarily aims to detect credit card fraud in the real world. Today, our lives have become more and more dependent on online transactions. As technology advances, the number of fraud cases also increases, and ultimately, a fraud detection algorithm needs to be developed to accurately find and eradicate fraudulent activity. Some Machine Learning algorithms can be applied to collect data to address this problem. These machine learning algorithms ultimately optimize the accuracy of the result data. Technique performance is evaluated based on accuracy, f1 score, and precision and recall. Then, processing some of the technique provided attributes identifies the fraud detection and provides the visualization of the graphical model. Classification based algorithms such as logistic regression, random forest and KNN for processing highly unbalanced datasets.
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