For example, households can be classified into those that have pets and those that don’t. Regression: is where an actual number is output, for example calculating the average number of pets per ...

A random forest consisting of 1,000 decision trees was trained on the six remaining outbreaks linked to forest loss and a random sample of 24 out of the 28 locations in the second and third data ...

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.

Decision tree regression is a fundamental technique that can be used by itself, and is also the basis for powerful ensemble techniques (a collection of many decision trees), notably, AdaBoost ...

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 ...