srowen commented on a change in pull request #27097: [SPARK-9478][ML][PYSPARK]
Add sample weights to Random Forest
URL: https://github.com/apache/spark/pull/27097#discussion_r363575497
##########
File path:
mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
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@@ -69,6 +67,10 @@ class RandomForestClassifier @Since("1.4.0") (
@Since("1.4.0")
def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode,
value)
+ /** @group setParam */
+ @Since("3.0.0")
+ def setMinWeightFractionPerNode(value: Double): this.type =
set(minWeightFractionPerNode, value)
Review comment:
Yes, I mean more from an API perspective, they are setting the 'same thing',
sort of. The weighted value is a generalization of the existing parameter.
Would you set both, really? maybe the existing setter just sets the new value
too. The check against weight vs minimum weight, when weights are all 1.0,
would be the same. Is that simpler?
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