Decision Tree
topic on 3 shows · 4 statements across 3 episodes
Capital Allocators 
the MAD Podcast 
the a16z Podcast
4 statements about Decision Tree, every show
Mahr: Factor selection and interaction at MDT is 100% algorithmic
“The selection of factors is driven by the potential questions that can be asked, is driven by the investment team. That's a major area of focus for us on the research side. Once we present that list of factors to the algorithm, it's Completely mechanically det…”
Mahr: MDT limits decision trees to two to five questions to avoid fragmentation
“Typically we ask between two and five questions in each tree. The reason we don't ask more questions is we found that as you ask questions deeper and deeper in the tree, you're working on smaller and smaller pools of data because the trees are customized to th…”
Chen: Deep neural networks outperform decision trees but are inherently undebuggable
“In a decision tree, you can actually examine the decision tree and understand why a system made any single decision. Very, very easy to debug. The bummer is decision trees don't get you very good results. And so these deep networks get you much better results,…”