CREDIT CARD FRAUD DETECTION USING RANDOM FOREST CLASSIFIER
M. SUSHMA, INDU VADANA CIGA, G.V. DEVAKI NANDAN, A. SATISH KUMAR · Zenodo (CERN European Organization for Nuclear Research) · 2022
In huge organizations, transactions take place constantly. There are studies which show that fraudulent transactions take place quite often. This causes significant amount of damage to the customers and the organizations due to loss of trust. It is not sensible to investigate every transaction mainly because it is highly time consuming which leads to customers exasperated. In our project, we are focusing on credit card fraud detection in the real-world. There are already many approaches taken to reduce and detect the credit card fraud transactions. The results of these are not very accurate. Our approach in improving the accuracy is using popular machine learning algorithm that belongs to supervised learning technique. Based on Accuracy, specificity, sensitivity and precision of the techniques, its performance is evaluated.