Github user chouqin commented on the pull request:
https://github.com/apache/spark/pull/2341#issuecomment-55216875
@jkbradley Thanks for your nice work, I have read your code and just have
one question:
Can we allocate a root node before the loop in `train()`, and allocate left
and child node for the next level after choosing split, then
`DecisionTree.findBestSplits` can just return `doneTraining`. During the choose
splits step which iterate all the nodes, it just set fields of current node,
and don't allocate a new node. This seems to be more easier to understand for
me, because it handle all levels in a same way.
What's more, I think after choosing a best split and allocate left and
right child nodes, we can set impurity of left and right child, which can avoid
recomputation of impurity in `calculateGainForSplit`, this saving may be
useless when (number of splits * number of features * number of classes) is
small though.
This is just a suggestion, ignore this if you don't think it helps :).
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