Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/15450#discussion_r84776242
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala ---
@@ -85,9 +101,50 @@ class KMeansSuite extends SparkFunSuite with
MLlibTestSparkContext {
Vectors.dense(1.0, 3.0, 4.0)),
2)
- // Make sure code runs.
- var model = KMeans.train(data, k = 3, maxIterations = 1)
- assert(model.clusterCenters.size === 3)
+ var model = KMeans.train(data, k = 3, maxIterations = 1,
initializationMode = "random")
+ assert(model.clusterCenters.length === 2)
+
+ model = KMeans.train(data, k = 3, maxIterations = 1,
initializationMode = "k-means||")
+ assert(model.clusterCenters.length === 2)
+ }
+
+ test("unique cluster centers") {
+ val rng = new scala.util.Random(42)
+ val points = (0 until 10).map(i =>
Vectors.dense(Array.fill(3)(rng.nextDouble)))
+ val data = sc.parallelize(
+ points.flatMap { point =>
+ Array.fill(rng.nextInt(4))(point)
+ }, 2
+ )
+ val norms = data.map(Vectors.norm(_, 2.0))
+ val zippedData = data.zip(norms).map { case (v, norm) =>
+ new VectorWithNorm(v, norm)
+ }
+ // less centers than k
+ val km = new KMeans().setK(50)
+ .setMaxIterations(10)
+ .setInitializationMode("k-means||")
+ .setInitializationSteps(10)
+ .setSeed(42)
+ val initialCenters = km.initKMeansParallel(zippedData).map(_.vector)
+ assert(initialCenters.length === initialCenters.distinct.length)
+
+ val model = km.run(data)
+ val finalCenters = model.clusterCenters
+ assert(finalCenters.length === finalCenters.distinct.length)
+
+ // run local k-means
+ val km2 = new KMeans().setK(10)
+ .setMaxIterations(10)
+ .setInitializationMode("k-means||")
+ .setInitializationSteps(10)
+ .setSeed(42)
+ val initialCenters2 = km2.initKMeansParallel(zippedData).map(_.vector)
+ assert(initialCenters2.length === initialCenters2.distinct.length)
+
+ val model2 = km.run(data)
--- End diff --
should be `val model2 = km2.run(data)`
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