Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/582#issuecomment-41749238
I prefer removing the miniBatchFraction. Those quasi-Newton methods
approximate the inverse of Hessian. It doesn't make sense if the gradients are
computed from a varying objective.
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