Explainable machine learning models for Medicare fraud detection

Abstract As a means of building explainable machine learning models for Big Data, we apply a novel ensemble supervised feature selection technique. The technique is applied to publicly available insurance claims data from the United States public health insurance program, Medicare. We approach Medic...

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Egile Nagusiak:	John T. Hancock, Richard A. Bauder, Huanjing Wang, Taghi M. Khoshgoftaar
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	SpringerOpen 2023-10-01
Saila:	Journal of Big Data
Gaiak:	Big Data Class imbalance Explainable machine learning models Ensemble supervised feature selection Medicare fraud detection
Sarrera elektronikoa:	https://doi.org/10.1186/s40537-023-00821-5
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Explainable machine learning models for Medicare fraud detection

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