Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17862#discussion_r115698645
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala ---
@@ -205,15 +233,21 @@ class LinearSVC @Since("2.2.0") (
val costFun = new LinearSVCCostFun(instances, $(fitIntercept),
$(standardization), bcFeaturesStd, regParamL2, $(aggregationDepth))
- def regParamL1Fun = (index: Int) => 0D
- val optimizer = new BreezeOWLQN[Int, BDV[Double]]($(maxIter), 10,
regParamL1Fun, $(tol))
+ val optimizerAlgo = $(optimizer) match {
--- End diff --
Personally I would be in favor of making square hinge the default with
L-BFGS. But we would need to make it clear to users that if they select the
pure hinge loss then there is a risk involved in using L-BFGS rather than
OWL-QN.
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