Random Forest Regression

• Random Forest is an ensemble of decision trees, where each tree asks multiple yes/no questions to reach a decision. Overfitting is a problem found in decision trees, however, by using many decision trees and averaging their results, Random Forest reduces the amount of overfitting.
• They are very powerful, often work well without heavy tuning of the parameters. Random forests usually work well on large datasets, and training can easily be parallelized over many CPU cores within a powerful computer.