Github user sethah commented on a diff in the pull request: https://github.com/apache/spark/pull/14717#discussion_r75519309 --- Diff: mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala --- @@ -256,6 +256,15 @@ class LogisticRegression @Since("1.2.0") ( @Since("1.5.0") override def getThresholds: Array[Double] = super.getThresholds + /** + * Set suggested depth for treeAggregate or treeReduce (>= 2). + * Default is 2. + * @group setParam --- End diff -- I'm not suggesting you implement the logic to automatically decide what depth is best. Typically parameters like these that require a user to understand how this algorithm is implemented (i.e. that it uses a treeAggregation to collect gradient updates) we make "expertParam."
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