Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/9912#discussion_r55147885
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala
---
@@ -167,19 +167,15 @@ class RandomForestClassifierSuite extends
SparkFunSuite with MLlibTestSparkConte
.setSeed(123)
// In this data, feature 1 is very important.
- val data: RDD[LabeledPoint] = sc.parallelize(Seq(
- new LabeledPoint(0, Vectors.dense(1, 0, 0, 0, 1)),
- new LabeledPoint(1, Vectors.dense(1, 1, 0, 1, 0)),
- new LabeledPoint(1, Vectors.dense(1, 1, 0, 0, 0)),
- new LabeledPoint(0, Vectors.dense(1, 0, 0, 0, 0)),
- new LabeledPoint(1, Vectors.dense(1, 1, 0, 0, 0))
- ))
+ val data: RDD[LabeledPoint] = TreeTests.featureImportanceData(sc)
val categoricalFeatures = Map.empty[Int, Int]
val df: DataFrame = TreeTests.setMetadata(data, categoricalFeatures,
numClasses)
val importances = rf.fit(df).featureImportances
val mostImportantFeature = importances.argmax
assert(mostImportantFeature === 1)
+ assert(importances.toArray.sum === 1.0)
--- End diff --
I updated the feature importance tests here, as well, with additional
checks.
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