Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/643#discussion_r12333419
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala
---
@@ -40,6 +40,8 @@ class GradientDescent(private var gradient: Gradient,
private var updater: Updat
private var numIterations: Int = 100
private var regParam: Double = 0.0
private var miniBatchFraction: Double = 1.0
+ private var stochastic: Boolean = true
--- End diff --
Having both `miniBatchFaction` and `stochastic` is a little confusing. I
understand that you want to skip the sampling part. Can you do a check and skip
sampling if `miniBatchFraction >= 1.0`?
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