Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/10355#discussion_r47933679
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
---
@@ -100,6 +101,40 @@ class GBTClassifierSuite extends SparkFunSuite with
MLlibTestSparkContext {
Utils.deleteRecursively(tempDir)
}
+ test("GradientBoostedTrees should support all NumericType labels") {
+ val dfWithIntLabels =
TreeTests.setMetadata(sqlContext.createDataFrame(Seq(
--- End diff --
I'm wondering if there is some way to reuse the code here since we need to
implement roughly the same test (train with all different label column types,
check that they are the same as training with double type) for each different
predictor. Maybe adding something in a helper function under `MLTestingUtils`?
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