Utilization of Decision Tree in Prediction of Health Care Costs

Abstract

Prediction of health care cost has a big importance for general budget planning and accurate pricing of institutions which are in insurance sector. In particular, insurance companies need to make accurate analysis for competitive bidding and for increasing profitability. In this study, decision tree which is one of the data mining methods is used to make prediction of health care cost and results are analyzed. The values age, sex, number of child, bmi, region, smoker which taken from the data set given in open access Kaggle data mining data storage platform is input attributes. Health care cost is the label attribute depends on these attributes. Analysis of the decision tree method was performed in this prediction which is made by using these values. Performance results will hope to be helpful for planners on health budget, the insurance companies and researchers on those areas.

Keywords

• decision tree
• health care cost
• prediction
• data mining