Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r124399685
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -339,15 +364,16 @@ class GeneralizedLinearRegression @Since("2.0.0")
(@Since("2.0.0") override val
"GeneralizedLinearRegression was given data with 0 features, and
with Param fitIntercept " +
"set to false. To fit a model with 0 features, fitIntercept must
be set to true." )
- val w = if (!isDefined(weightCol) || $(weightCol).isEmpty) lit(1.0)
else col($(weightCol))
- val instances: RDD[Instance] =
- dataset.select(col($(labelCol)), w, col($(featuresCol))).rdd.map {
- case Row(label: Double, weight: Double, features: Vector) =>
- Instance(label, weight, features)
- }
+ val w = if (!isSetWeightCol(this)) lit(1.0) else col($(weightCol))
+ val offset = if (!isSetOffsetCol(this)) lit(0.0) else
col($(offsetCol)).cast(DoubleType)
val model = if (familyAndLink.family == Gaussian && familyAndLink.link
== Identity) {
// TODO: Make standardizeFeatures and standardizeLabel configurable.
+ val instances: RDD[Instance] =
+ dataset.select(col($(labelCol)), w, offset,
col($(featuresCol))).rdd.map {
+ case Row(label: Double, weight: Double, offset: Double,
features: Vector) =>
+ Instance(label - offset, weight, features)
+ }
val optimizer = new WeightedLeastSquares($(fitIntercept),
$(regParam), elasticNetParam = 0.0,
standardizeFeatures = true, standardizeLabel = true)
val wlsModel = optimizer.fit(instances)
--- End diff --
I would suggest we leave `WeightedLeastSquares` as is, since it is a
general purpose optimization tool and offset is more specific to GLM. I have
not seen a weighted least squares implementation that supports offset.
We discussed something relevant above
[here](https://github.com/apache/spark/pull/16699/files/d44974cfe50092bb639a31aa7aa9b16eb1d21fae#diff-6759d92c079f0957bfa814e339e10e7eR301
). I originally defined `val instances: RDD[OffsetInstance]` outside the
`ifelse` and then convert it to `RDD[Instance]` for the Gaussian identity link
case. But this will incur one extra map. There was some concern that this could
be expensive. However, if this extra conversion is not a big deal, I can revert
it back to that which is basically the implementation of the `OffsetInstance`
interface for `WeightedLeastSquares`.
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