imatiach-msft commented on a change in pull request #21632: 
[SPARK-19591][ML][MLlib] Add sample weights to decision trees
URL: https://github.com/apache/spark/pull/21632#discussion_r245547573
 
 

 ##########
 File path: mllib/src/main/scala/org/apache/spark/ml/feature/Instance.scala
 ##########
 @@ -26,7 +26,7 @@ import org.apache.spark.ml.linalg.Vector
  * @param weight The weight of this instance.
  * @param features The vector of features for this data point.
  */
-private[ml] case class Instance(label: Double, weight: Double, features: 
Vector)
+private[spark] case class Instance(label: Double, weight: Double, features: 
Vector)
 
 Review comment:
   it was used in 
mllib/src/main/scala/org/apache/spark/mllib/tree/RandomForest.scala when 
passing labeledpoint to new-style ml random forest, which required converting 
to ml Instance from mllib LabeledPoint.  Hence, I've added another run method 
on RandomForest in ml that takes the old-style mllib LabeledPoints and converts 
to Instances.

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