RITs Pseudocode

• The following is pseudocode to use for the RITs algorithm
• It is based on the original Meinshausen/ Shah paper

RITs inputs

• M Number of trees to build
• D Max Tree Depth
• p Children sample node probability threshold (= 0 for no split, i.e. based on uniform (0, 1) RNG with respect the the threshold)
• n Min number of children to sample at each node (if p != 0 then at each node if the split node prob <= p, then sample n children at that node, else sample n + 1 children at that node each node)

i.e. if we want just a binary RIT i.e. always 2 children sampled at each node then set p = 0 and n = 2.

RITs outputs

Our version of the RITs should output the following:

• Node class and The RIT class
• The random number list of nodes that we generated i.e. as a generator function (for reproducibility and testing)
• The entire RITs (for all M trees)

RIT Node class

• We need to return the rich RIT object
  • The authors mention calculating prevalence and sparsity, how should we best calculate these metrics?
  • Needs to return clean attributes:
    • IsNode
    • HasChildren
    • NumChildren
    • Is leaf node
    • getIntersectedPath

Summary

• At it's core, the RIT is comprised of 3 main modules
• FILTERING: Subsetting to either the 1's or the 0's
• RANDOM SAMPLING: The path-nodes in a weighted manner, with/ without replacement, within tree/ outside tree
• INTERSECTION: Intersecting the selected node paths in a systematic manner