RandomForests is a collection of many CART® trees that are not influenced by each other when constructed. The sum of the predictions made from decision trees determines the overall prediction of the forest.

Two forms of randomization occur in RandomForests, one by trees and one by node. At the tree level, randomization takes place via observations. At the node level, randomization occurs by using a randomly-selected subset of predictors. Each tree is grown to a maximal size and left unpruned. This process is repeated until a user-defined number of trees is created, a collection called a random forest. Once this is created, the predictions for each tree are used in a “voting” process. The overall prediction is determined by voting for classification and by averaging for regression.