Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/16441
Thanks for the PR; I do want to get this fixed. However, I don't think
this is the right way to make predictions of probabilities for GBTs. I believe
it should depend on the loss used. E.g., check out page 8 of Friedman (1999)
"Greedy Function Approximation? A Gradient Boosting Machine"
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