A Computational Intelligence Approach for Predicting Medical Insurance Cost

Table 5

Outcomes of machine learning models.

Model	RMSE	R2_score (training)	R2_score (test)	Cross-validation
Linear Regression	0.479808	0.741410	0.782694	0.744528
Ridge Regressor	0.465206	0.741150	0.783800	0.825999
Support Vector Regression	0.358771	0.847234	0.871283	0.842307
Random Forest Regressor	0.347522	0.874422	0.879228	0.849299
Stochastic Gradient Boosting	0.340189	0.17448	0.898595	0.858293
XGBoost	0.342509	0.831859	0.883683	0.853654
Decision Tree (CART)	0.363336	0.820118	0.873213	0.833492
Multiple Linear Regression	0.409725	0.74636	0.794312	0.755814
k-Nearest Neighbors	0.726835	0.274117	0.356719	0.318517