In random forests another source of diversity is introduced when the set of predictor variables to select from is randomly restricted in each split, producing even more diverse trees. The number of randomly preselected splitting variables, termed mtry in most algorithms, as well as the overall number of trees, usually termed ntree, are parameters of random forests that affect the stability of the results and will be discussed further in section “Features and pitfalls”. Obviously random forests include bagging as the special case where the number of randomly preselected splitting variables is equal to the overall number of variables.
