Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/292
Title: Credit Card Fraud Detection - Machine Learning methods
Authors: Varmedja D.
Karanović, Mirjana 
Sladojević, Srđan 
Arsenović, Marko 
Anderla, Andraš 
Issue Date: 16-May-2019
Journal: 2019 18th International Symposium INFOTEH-JAHORINA, INFOTEH 2019 - Proceedings
Abstract: © 2019 IEEE. Credit card fraud refers to the physical loss of credit card or loss of sensitive credit card information. Many machine-learning algorithms can be used for detection. This research shows several algorithms that can be used for classifying transactions as fraud or genuine one. Credit Card Fraud Detection dataset was used in the research. Because the dataset was highly imbalanced, SMOTE technique was used for oversampling. Further, feature selection was performed and dataset was split into two parts, training data and test data. The algorithms used in the experiment were Logistic Regression, Random Forest, Naive Bayes and Multilayer Perceptron. Results show that each algorithm can be used for credit card fraud detection with high accuracy. Proposed model can be used for detection of other irregularities.
URI: https://open.uns.ac.rs/handle/123456789/292
ISBN: 9781538670736
DOI: 10.1109/INFOTEH.2019.8717766
Appears in Collections:FTN Publikacije/Publications

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