Random Forest

A supervised machine learning (see also supervised learning) algorithm that builds multiple decision trees and merges them to get a more accurate and stable prediction. Each decision tree is built with a random subset of the training data (see also bootstrap aggregating), hence the name random forest. Random forests are helpful to use with datasets that are missing values or are very complex.