Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/7099#discussion_r34015538
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
@@ -212,12 +230,139 @@ class LinearRegressionModel private[ml] (
extends RegressionModel[Vector, LinearRegressionModel]
with LinearRegressionParams {
+ @transient private var trainingSummary:
Option[LinearRegressionTrainingSummary] = None
--- End diff --
If we make the whole thing `transient`, does it mean even the small object
like `lossHistory` can not be saved as part of model? I'm still leaning toward
having lossHistory as part of LinearRegressionModel, and link to training
dataframe using @transient. In fact, in R, those small stats are part of models.
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