Combining trees with CART
Salford CART allows one to choose from several ways of combining
separate CART trees into a single predictive engine. The
trees are combined by either averaging their outputs for
regression or by using an unweighted plurality voting scheme
for classification. The current version of CART offers two
combination methods: Bootstrap aggregation and ARCing. Each
generates a set of trees by resampling (with replacement)
from the original training data.