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5. Credit Card Fraud Detection and Prevention using Machine Learning

Author

K. Saran Sriram, D. Piyush, R. A. Karthikeyan, H. Sangeetha, S. Abinayaa, and Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)

Subjects
Environmental Engineering, Computer science, business.industry, D7327049420/2020©BEIESP, Credit card fraud, General Engineering, 2249-8958, Machine learning, computer.software_genre, Computer Science Applications, Random forest, Sensitivity (control systems), Artificial intelligence, Accuracy, Fraud Detection, Precision, Random Forest Algorithm, Sensitivity, business, computer
Abstract

This research focused mainly on detecting credit card fraud in real world. We must collect the credit card data sets initially for qualified data set. Then provide queries on the user's credit card to test the data set. After random forest algorithm classification method using the already evaluated data set and providing current data set[1]. Finally, the accuracy of the results data is optimised. Then the processing of a number of attributes will be implemented, so that affecting fraud detection can be found in viewing the representation of the graphical model. The techniques efficiency is measured based on accuracy, flexibility, and specificity, precision. The results obtained with the use of the Random Forest Algorithm have proved much more effective.

Published
2020

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