Github user srowen commented on the issue:
https://github.com/apache/spark/pull/17503
I was saying that I thought the nodes had more info than just the
majority-class prediction. If they did, then they're much more rarely
combinable, because they vary in more than just their prediction. They _don't_
have a distribution over class labels or something like that, but they do carry
impurity info. Can you merge two nodes with different impurity but the same
prediction? this could be a dumb question, I actually am not sure if impurity
info is even used after training.
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