For more information on this research see: Comparison and Analysis of the Effectiveness of Linear Regression, Decision Tree, and Random Forest Models for Health Insurance Premium Forecasting.

We developed a modeling approach for seasonal streamflow forecasts using a machine learning technique, random forest (RF), for runoff season flows (April 1–July 31 total) at the important gauge of ...

The study compares two models: random forest and support vector classifiers. The identification of potential natural gas price drivers that improve the model’s classification is crucial. The forecast ...