  Recursive partitioning is the core of several statistical methods including
CART, random forest, and boosted trees. Despite the popularity of tree based
methods, to date, there did not exist methods for combining multiple trees into
a single tree, or methods for systematically quantifying the discrepancy
between two trees. Taking advantage of the recursive structure in trees we
formulated fast algorithms for computing affine combinations, distances and
correlations in a vector subspace of recursive partition functions.
