Reading this I got several dejavus to my grad school classes on classical ML stuff. I like the direction but it feels like it could be better if it admitted that it's a variant of decision tree embedding, and built on some of the massive amount of research work in that area. At least in terms of understanding.
I suspect doing a random forest version of this would actually help. Perhaps we will see this as a legit pre-training step.
Also called Perfect Decision Tree.