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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