Abstract

Abstract: Healthcare expenditure is a critical concern worldwide, and accurate prediction of health insurance costs can aid in effective resource allocation and risk management. In this project, we employ machine learning (ML) techniques to develop a predictive model forestimating health insurance costs. The dataset used comprises various demographic, lifestyle, andmedical information of insured individuals,including lifetime, gender, QTI, smoking habits, area, and medical history.

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