Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/6386#discussion_r30955509
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -106,6 +106,11 @@ class LogisticRegression(override val uid: String)
case LabeledPoint(label: Double, features: Vector) => (label,
features)
}
val handlePersistence = dataset.rdd.getStorageLevel ==
StorageLevel.NONE
+ trainOnInstances(instances, handlePersistence)
+ }
+
+ protected[spark] def trainOnInstances(instances: RDD[(Double, Vector)],
--- End diff --
I don't think thats whats going on under the hood in `ALS.scala` - its
passing in an RDD of `NewALS.Rating` case classes, which is the datatype that
`NewALS'` train function works on (although I'm never completely sure with
implicits). If I simply try and pass the RDD of LabeledPoints its a compile
error (although I could be missing one of the implicit imports but I'm not sure
which one).
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