Performance Evaluation of Machine Learning Algorithms for Credit Card Fraud Detection


Credit card transactions have become common place today and so is the frauds associated with it. One of the most common modus operandi to carry out fraud is to obtain the card information illegally and use it to make online purchases. For credit card companies and merchants, it is in-feasible to detect these fraudulent transactions among thousands of normal transactions. If sufficient data is collected and made available, machine learning algorithms can be applied to solve this problem. In this work, popular supervised and unsupervised machine learning algorithms have been applied to detect credit card frauds in a highly imbalanced dataset. It was found that unsupervised machine learning algorithms can handle the skewness and give best classification results.



Machine learning algorithms

Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL