IDENTIFYING FRAUD IN ONLINE TRANSACTIONS

Fraudulent credit card transactions must be when customers are charged for items that they did not purchase. Such problems can tackled with Data Science and its importance, along Machine Learning, cannot overstated. This project intends to illustrate the modelling of a data set using machine learning Identifying Fraud in Online Transactions. The Transactions problem includes past ones turned out fraud. model is then used recognize whether new transaction fraudulent or not. Our objective here detect 99.99% while minimizing incorrect fraud classifications. typical sample classification. In this process, we have focused on analyzing pre-processing sets by Random Forest Algorithm.