Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/16158#discussion_r131340257
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -133,7 +134,10 @@ class CrossValidator @Since("1.2.0") (@Since("1.4.0")
override val uid: String)
logInfo(s"Best cross-validation metric: $bestMetric.")
val bestModel = est.fit(dataset, epm(bestIndex)).asInstanceOf[Model[_]]
instr.logSuccess(bestModel)
- copyValues(new CrossValidatorModel(uid, bestModel,
metrics).setParent(this))
+ val model = new CrossValidatorModel(uid, bestModel,
metrics).setParent(this)
+ val summary = new TuningSummary(epm, metrics, bestIndex)
+ model.setSummary(Some(summary))
--- End diff --
Are there other obvious things that might go into the summary in future,
that would make a `TuningSummary` class a better fit?
Future support for say, multiple metrics, could simply extend the dataframe
columns so that is ok. But is there anything else you can think of?
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