Explainable machine learning models for Medicare fraud detection

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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Bibliographic Details
Main Authors: John T. Hancock, Richard A. Bauder, Huanjing Wang, Taghi M. Khoshgoftaar
Format: Article
Language:English
Published: SpringerOpen 2023-10-01
Series:Journal of Big Data
Subjects:
Big Data
Class imbalance
Explainable machine learning models
Ensemble supervised feature selection
Medicare fraud detection
Online Access:https://doi.org/10.1186/s40537-023-00821-5

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