Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/8884#discussion_r40569761
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
@@ -199,8 +238,8 @@ class LinearRegression(override val uid: String)
val costFun = new LeastSquaresCostFun(instances, yStd, yMean,
$(fitIntercept),
$(standardization), featuresStd, featuresMean, effectiveL2RegParam)
-
- val optimizer = if ($(elasticNetParam) == 0.0 || effectiveRegParam ==
0.0) {
--- End diff --
Owlqn is an generalized version of lbfgs but can solve L1. So when the
solver is lbfgs, and L1 is used, we should use owlqn.
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