On the other hand, random forest and bagging tree regression models seem to have a good reputation among machine learning practitioners (most of my colleagues at least) because the models often work ...

Recent scientific article explores the use of machine learning techniques to identify the key risk factors associated with ...

Therefore, random forest regression is a very effective method for health insurance prediction. The next model is the linear regression model with a model score of 0.7584.

6. Random forest models - Similar to gradient boosting, random forest models use a combination of simpler models, mainly decision trees.

In an age where data drives decisions and automation defines excellence, the insurance industry stands at the cusp of a digital renaissance. At the ...