IRJET- Credit Card Fraud Detection using Isolation Forest

This document discusses using machine learning algorithms like Isolation Forest and Local Outlier Factor to detect credit card fraud. It begins with an introduction to the increasing problem of credit card fraud and challenges in detecting fraudulent transactions among millions occurring daily. The document then provides background on supervised and unsupervised machine learning algorithms and describes how Isolation Forest and Local Outlier Factor work. Related work discussing other fraud detection techniques and the limitations of existing approaches is also summarized. The goal of the paper is to compare Isolation Forest and Local Outlier Factor to determine the most effective algorithm for credit card fraud detection.