The demo creates a random forest regression model, evaluates the model accuracy on the training and test data, and then uses the model to predict the target y value for x = [-0.1660, 0.4406, -0.9998, ...

Medical datasets often present a major challenge for machine learning models: skewness in continuous variables such as age, ...

We evaluated four statistical models-Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS)-for predictive vegetation mapping ...

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.

The Annals of Statistics, Vol. 43, No. 4 (August 2015), pp. 1716-1741 (26 pages) Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5-32] that combines several ...