Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r98018075
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -753,14 +794,15 @@ class GeneralizedLinearRegressionModel private[ml] (
}
override protected def transformImpl(dataset: Dataset[_]): DataFrame = {
- val predictUDF = udf { (features: Vector) => predict(features) }
- val predictLinkUDF = udf { (features: Vector) => predictLink(features)
}
+ val predictUDF = udf { (features: Vector, offset: Double) =>
predict(features, offset) }
+ val predictLinkUDF = udf { (features: Vector, offset: Double) =>
predictLink(features, offset) }
+ val off = if (!isSet(offsetCol) || $(offsetCol).isEmpty) lit(0.0) else
col($(offsetCol))
--- End diff --
also, as I mentioned above, if family = Gaussian and link = Identity we
shouldn't be passing any offset, but then the user shouldn't be setting an
offset column probably - so either adding that to the validation logic or to
the code here or to the predict function you call below would fix this unusual
case; I think this seems like a validation issue and probably should be added
to the validation method.
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