where I is the indicator function, yielding 1 if x, y ∈ S are in the same block of a partition ρ and else 0. A RF can be viewed as a partitioning distribution, which partitions the data along the height of its trees. At the root of every decision tree, every element in S is part of the same block. Therefore, all combinations of two data instances share the block in that partition. Figure shows the other partitions generated by one decision tree. It is possible to sample from this distribution by randomly selecting trees and depths and then checking if two data points share the same block. Figure : Decision tree dividing the data set into three partitions.