Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/3636#discussion_r21480867
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala
---
@@ -39,6 +41,7 @@ class GradientDescent private[mllib] (private var
gradient: Gradient, private va
private var numIterations: Int = 100
private var regParam: Double = 0.0
private var miniBatchFraction: Double = 1.0
+ private var convergenceTolerance: Double = 0.0
--- End diff --
I feel like the default should be > 0.0. Something small like 0.001 (a
value pulled from libsvm
[https://github.com/cjlin1/libsvm/blob/master/python/svm.py]) might be
reasonable. Basically, I think that convergence tolerance is generally a
better stopping criterion than numIterations, and having it > 0.0 will give it
a chance of taking effect before numIterations.
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