Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/12574#discussion_r61081248
--- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
---
@@ -200,8 +240,42 @@ class ALSModel private[ml] (
@Since("1.3.0")
def setPredictionCol(value: String): this.type = set(predictionCol,
value)
+ /** @group setParam */
@Since("2.0.0")
+ def setLabelCol(value: String): this.type = set(labelCol, value)
+
+ /** @group setParam */
+ @Since("2.0.0")
+ def setK(value: Int): this.type = set(k, value)
+
+ /** @group setParam */
+ @Since("2.0.0")
+ def setRecommendFor(value: String): this.type = set(recommendFor, value)
--- End diff --
That's interesting. I like the idea, though no other estimator/model uses
this approach (but AFAIK there's no other estimator where 2 specific
non-default params *must* be set together). @jkbradley @holdenk thoughts?
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