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Credit Card Fraud Detection using Machine Learning Methodology

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.8, No. 3)

Publication Date:

Authors : ; ;

Page : 257-260

Keywords : ML; Classification; Data processing; supervised; learning;

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The speedy participation in online primarily based transactional activities raises the fallacious cases everywhere and causes tremendous losses to the personal and financial business. [1] Although several criminal activities are occurring in commercial business, fraudulent e-card activities are among the foremost prevailing and disturbed regarding by online customers. Data processing techniques were used to check the patterns and characteristics of suspicious and non-suspicious transactions supported normalized and anomalies knowledge. On the opposite hand, machine learning (ML) techniques were used to predict the suspicious and non-suspicious transactions mechanically by victimization classifiers [2][5]. This paper discusses the supervised based mostly classification. When preprocessing the dataset using normalization and Principal element Analysis, all the classifiers achieved over 95.0% accuracy compared to results reached before preprocessing the dataset.

Last modified: 2019-03-23 02:50:54