Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/11119#discussion_r56110707
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---
@@ -108,6 +111,21 @@ class KMeansSuite extends SparkFunSuite with
MLlibTestSparkContext with DefaultR
val kmeans = new KMeans()
testEstimatorAndModelReadWrite(kmeans, dataset,
KMeansSuite.allParamSettings, checkModelData)
}
+
+ test("Initialize using given cluster centers") {
+ val kmeans = new KMeans()
+ .setK(k)
+ .setSeed(1)
+ .setMaxIter(1000) // Set a fairly high maxIter to make sure the
model is converged.
--- End diff --
This sounds expensive. What if instead we did this:
* a = KMeans with 1 iteration
* b = KMeans with 2 iterations
* c = KMeans with initialModel a, with 1 iteration
* ensure b and c are equal
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