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  • 标题:Machine Learning Model for Credit Card Fraud Detection- A Comparative Analysis
  • 本地全文:下载
  • 作者:Pratyush Sharma ; Souradeep Banerjee ; Devyanshi Tiwari
  • 期刊名称:The International Arab Journal of Information Technology
  • 印刷版ISSN:1683-3198
  • 出版年度:2021
  • 卷号:18
  • 期号:6
  • DOI:10.34028/iajit/18/6/6
  • 语种:English
  • 出版社:Zarqa Private University
  • 摘要:In today's world, we are on an express train to a cashless society which has led to a tremendous escalation in the use of credit card transactions. But the flipside of this is that fraudulent activities are on the increase; therefore, implementation of a methodical fraud detection system is indispensable to cardholders as well as the card-issuing banks. In this paper, we are going to use different machine learning algorithms like random forest, logistic regression, Support Vector Machine (SVM), and Neural Networks to train a machine learning model based on the given dataset and create a comparative study on the accuracy and different measures of the models being achieved using each of these algorithms. Using the comparative analysis on the F_1 score, we will be able to predict which algorithm is best suited to serve our purpose for the same. Our study concluded that Artificial Neural Network (ANN) performed best with an F_1 score of 0.91.
  • 关键词:Machine learning;credit card fraud detection;random forest;accuracy;neural network;SVM
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