Enhancing Performance of Credit Card Model by Utilizing LSTM Networks and XGBoost Algorithms

This research paper presents novel approaches for detecting credit card risk through the utilization of Long Short-Term Memory (LSTM) networks and XGBoost algorithms. Facing the challenge of securing credit card transactions, this study explores the potential of LSTM networks for their ability to un...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Kianeh Kandi, Antonio García-Dopico
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	MDPI AG 2025-02-01
Σειρά:	Machine Learning and Knowledge Extraction
Θέματα:	recurrent neural network (RNN) long short-term memory (LSTM) network extreme gradient boosting (XGBoost) synthetic minority oversampling technique (SMOTE) imbalanced dataset
Διαθέσιμο Online:	https://www.mdpi.com/2504-4990/7/1/20
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