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Title

Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble

  Khadija Shazly 1 * ,   Nima Khodadadi 2

1  Faculty of Computer and Information, Mansoura university, Egypt
    (:khadijashazly@students.mans.edu.eg)

2  University of Miami, 1251 Memorial Drive, Coral Gables, 33146, FL, USA
    (nxk682@miami.edu)


Doi   :   https://doi.org/10.54216/JAIM.020105

Received: May 11, 2022 Accepted: October 26, 2022

Abstract :

Credit card use is rapidly increasing as a result of the widespread availability of these cards, the ease of making electronic transfers, and the ubiquity of online shopping. But credit card debt poses a serious risk to businesses and governments alike, not to mention individual savers and investors. Consequently, the need for efficient, timely, and reliable ways to anticipate credit card risk has grown. In this study, we offer a framework that combines three classifiers, namely, support vector machines, multilayer perceptron and decision trees, to improve the network's accuracy. The proposed strategy is shown to be very competitive with others through simulation.

Keywords :

Credit scoring; Credit card; Machine learning; Classification; Metaheuristic optimization; K-Nearest neighbor; Random Forest; Support vector machines

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Cite this Article as :
Style #
MLA Khadija Shazly , Nima Khodadadi. "Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble." Journal of Artificial Intelligence and Metaheuristics, Vol. 2, No. 1, 2022 ,PP. 46-54 (Doi   :  https://doi.org/10.54216/JAIM.020105)
APA Khadija Shazly , Nima Khodadadi. (2022). Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble. Journal of Journal of Artificial Intelligence and Metaheuristics, 2 ( 1 ), 46-54 (Doi   :  https://doi.org/10.54216/JAIM.020105)
Chicago Khadija Shazly , Nima Khodadadi. "Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble." Journal of Journal of Artificial Intelligence and Metaheuristics, 2 no. 1 (2022): 46-54 (Doi   :  https://doi.org/10.54216/JAIM.020105)
Harvard Khadija Shazly , Nima Khodadadi. (2022). Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble. Journal of Journal of Artificial Intelligence and Metaheuristics, 2 ( 1 ), 46-54 (Doi   :  https://doi.org/10.54216/JAIM.020105)
Vancouver Khadija Shazly , Nima Khodadadi. Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble. Journal of Journal of Artificial Intelligence and Metaheuristics, (2022); 2 ( 1 ): 46-54 (Doi   :  https://doi.org/10.54216/JAIM.020105)
IEEE Khadija Shazly, Nima Khodadadi, Credit Card Clients Classification Using Hybrid Guided wheel with Particle Swarm Optimized for Voting Ensemble, Journal of Journal of Artificial Intelligence and Metaheuristics, Vol. 2 , No. 1 , (2022) : 46-54 (Doi   :  https://doi.org/10.54216/JAIM.020105)