Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/18118#discussion_r149761025
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala ---
@@ -166,6 +166,40 @@ class GBTRegressorSuite extends SparkFunSuite with
MLlibTestSparkContext
}
/////////////////////////////////////////////////////////////////////////////
+ // Tests of feature subset strategy
+
/////////////////////////////////////////////////////////////////////////////
+ test("Tests of feature subset strategy") {
+ val numClasses = 2
+ val gbt = new GBTRegressor()
+ .setMaxDepth(3)
+ .setMaxIter(5)
+ .setSubsamplingRate(1.0)
+ .setStepSize(0.5)
+ .setSeed(123)
+ .setFeatureSubsetStrategy("all")
+
+ // In this data, feature 1 is very important.
+ val data: RDD[LabeledPoint] = TreeTests.featureImportanceData(sc)
+ val categoricalFeatures = Map.empty[Int, Int]
+ val df: DataFrame = TreeTests.setMetadata(data, categoricalFeatures,
numClasses)
+
+ val importances = gbt.fit(df).featureImportances
+ val mostImportantFeature = importances.argmax
+ assert(mostImportantFeature === 1)
+ assert(importances.toArray.sum === 1.0)
+ assert(importances.toArray.forall(_ >= 0.0))
+
+ // GBT with different featureSubsetStrategy
+ val gbtWithFeatureSubset = gbt.setFeatureSubsetStrategy("1")
+ val importanceFeatures =
gbtWithFeatureSubset.fit(df).featureImportances
+ val mostIF = importanceFeatures.argmax
+ assert(!(mostImportantFeature === mostIF))
+ assert(importanceFeatures.toArray.sum === 1.0)
+ assert(importanceFeatures.toArray.forall(_ >= 0.0))
+ assert(!(importanceFeatures.toDense.values.deep ===
importances.toDense.values.deep))
--- End diff --
Same here - we can remove unnecessary assertions as per
https://github.com/apache/spark/pull/18118#discussion_r148096176
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