Prediction for Insurance Premiums Based on Random Forest and Multiple Linear Regression

Insurance benefit forecasting is very important for insurance, and research on insurance has been going all the time. This paper aims to find an efficient simple model predicting benefits based multiple linear regression machine learning scenarios. To be specific, in process of prediction, random forest are used as prediction models. Through comparison analysis results, it found that more accurate results but lacks interpretability. Although not forest, can clearly explain facilitate discussion. two models have their own advantages. Based analysis, they provide some help referring whether use these These shed light guiding further exploration a way.