Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/9008#discussion_r53092821
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala
---
@@ -275,6 +278,63 @@ class DecisionTreeClassifierSuite extends
SparkFunSuite with MLlibTestSparkConte
val model = dt.fit(df)
}
+ test("training with weighted data") {
+ val (dataset, weightedDataset) = {
+ val testData1 = TreeTests.generateNoisyData(5, 123)
+ val testData2 = TreeTests.generateNoisyData(5, 456)
+
+ // Over-sample the 1st dataset twice.
+ val overSampledTestData1 = testData1.flatMap {
+ labeledPoint => Iterator(labeledPoint, labeledPoint)
+ }
+
+ val rnd = new Random(8392)
+ val weightedTestData1 = testData1.flatMap {
--- End diff --
It is not obvious what the code is doing here. A comment might be useful to
point out that you are weighting each sample by 2x, effectively, by using
weighted?
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