Github user facaiy commented on a diff in the pull request:
https://github.com/apache/spark/pull/19666#discussion_r149313427
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala ---
@@ -631,6 +614,42 @@ class RandomForestSuite extends SparkFunSuite with
MLlibTestSparkContext {
val expected = Map(0 -> 1.0 / 3.0, 2 -> 2.0 / 3.0)
assert(mapToVec(map.toMap) ~== mapToVec(expected) relTol 0.01)
}
+
+ test("traverseUnorderedSplits") {
+
--- End diff --
Since `traverseUnorderedSplits` is a private method, I wonder whether we
can check the unorder splits on DecisonTree directly? For example, create a
tiny dataset and generate a shallow tree (depth = 1?). I know the test case is
difficult (maybe impossible) to design, however it focuses on behavior instead
of implementation.
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