Dismantling Binary Opposition in Fraud Detection: A Fuzzy Deep Learning Framework for Imbalanced Transaction Data

In the context of behavioral finance, detecting credit card fraud remains a critical challenge, particularly when dealing with highly imbalanced datasets and ambiguous transaction patterns. This complexity highlights the limitations of traditional fraud detection models, which rely on a rigid binary...

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Xehetasun bibliografikoak
Egile Nagusiak:	Reham M. Essa, Yasser El-Kassrawy, Amer Alaya, Nevien El-Kassrawy
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2026-04-01
Saila:	Risks
Gaiak:	credit fraud detection uncertainty-aware systems fuzzy logic deep learning imbalanced data
Sarrera elektronikoa:	https://www.mdpi.com/2227-9091/14/5/98
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Dismantling Binary Opposition in Fraud Detection: A Fuzzy Deep Learning Framework for Imbalanced Transaction Data

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