Nataliya Shakhovska1, Nataliia Melnykova1,*, Valentyna Chopiyak2, Michal Gregus ml3
CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3969-3984, 2022, DOI:10.32604/cmc.2022.019882
Abstract The paper reports three new ensembles of supervised learning predictors for managing medical insurance costs. The open dataset is used for data analysis methods development. The usage of artificial intelligence in the management of financial risks will facilitate economic wear time and money and protect patients’ health. Machine learning is associated with many expectations, but its quality is determined by choosing a good algorithm and the proper steps to plan, develop, and implement the model. The paper aims to develop three new ensembles for individual insurance costs prediction to provide high prediction accuracy. Pierson coefficient and Boruta algorithm are used… More >
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