Github user dbtsai commented on the pull request:
https://github.com/apache/spark/pull/4593#issuecomment-74805610
Sorry for the late reply since I'm traveling recently. My concern is that
will this cause "caching twice" in the new ML api? For example, in
ml/classification/LogisticRegression.scala, the data is persisted before any
transformation, and then we cache the data again after the feature
transformation. Should we remove the persist in ml package and just cache it
after feature transformation here?
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