Ensembles of Grafted Trees

Grafted trees are trees that are constructed using two methods. The first method creates an initial tree, while the second method is used to complete the tree. In this work, the first classifier is an unpruned tree from a 10% sample of the training data. Grafting is a method for constructing ensembles of decision trees, where each tree is a grafted tree. Grafting by itself is better than Bagging. Moreover, grafted trees can also be used with any other ensemble method. It is clearly beneficial for Bagging and Random Forests. When using grafted trees with Boosting, the results depends of the considered variant. The best overall method is Grafted Random Forest.