Rohit Amrutkar, Abhishek Chikurdekar, Atharv Salunke, Abhijeet Waghmare

Insurance is a policy that diminish or eradicate the expenditure loss appear due to various risk. Different factors may have an impact on the Insurance cost. Machine learning is a field of study that gives computers potential to adapt without human interference. Machine learning is widely used in insurance industry. Machine learning allow insurance companies to acknowledge the customers in a better way and create an insurance cover that victual to their needs and profile. In this paper, the propose system will examine the individuals health details to forecast the health insurance amount prediction and exhibit the insurance plans. Four regression models such as Linear Regression, Support Vector Regressor, Random Forest Regressor and Gradient Boosting have been implemented and their performance is measured using Mean Absolute Error, Root Mean Absolute Error and Coefficient of determination. Based on the analysis, it is found that the Gradient Boosting performs better than the other regression algorithms.

https://doi.org/10.58357/jedcs.2022.v1.i1.9