Github user yinxusen commented on the pull request:
https://github.com/apache/spark/pull/11486#issuecomment-193390578
@yanboliang @jkbradley
For this PR, I extract labels manually from labelCol. But I still don't
think it's good to make assumption first for labels to be 0-based and
continuous like `0.0, 1.0, 2.0, ...`. Sure we can use a `StringIndexer` to
re-index the labels if it does not match the assumption. But checking it is not
efficient. I suggest keeping labels in `ml.NaiveBayes`.
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