Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/15314#discussion_r82094763
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
@@ -186,7 +201,11 @@ class LinearRegression @Since("1.3.0")
(@Since("1.3.0") override val uid: String
override protected def train(dataset: Dataset[_]): LinearRegressionModel
= {
// Extract the number of features before deciding optimization solver.
val numFeatures =
dataset.select(col($(featuresCol))).first().getAs[Vector](0).size
- val w = if (!isDefined(weightCol) || $(weightCol).isEmpty) lit(1.0)
else col($(weightCol))
+ val w = if (!isDefined(weightCol) || $(weightCol).isEmpty) {
--- End diff --
The easy way would just be to switch weight to still be a shared param just
not a codegened one and implement that their.
Another possiblity would be adding a SQLColumn base param type with
supporting this kind of logic if more than just weight columns could benefit
from it.
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