Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/10274#discussion_r49394419
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala ---
@@ -94,8 +110,7 @@ private[ml] class WeightedLeastSquares(
if (standardizeFeatures) {
lambda *= aVar(j - 2)
}
- if (standardizeLabel) {
- // TODO: handle the case when bStd = 0
+ if (standardizeLabel && bStd != 0) {
--- End diff --
Thanks. As you said, we will expect non zero coefficients in this case, so
we don't have to match glmnet.
However, we may want to throw excpetion when standerizeLabe is true, and
ystd is zero since the problem is not well defined.
Thanks.
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