Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/11119#discussion_r77014377
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---
@@ -139,16 +145,32 @@ class KMeansSuite extends SparkFunSuite with
MLlibTestSparkContext with DefaultR
val kmeans = new KMeans()
testEstimatorAndModelReadWrite(kmeans, dataset,
KMeansSuite.allParamSettings, checkModelData)
}
+
+ test("Initialize using given cluster centers") {
--- End diff --
IMO, the best test here is to train a model on some sample dataset. Then
train a model using that initial model on the same dataset, and verify that it
converges in a single iteration. I don't think we have a way to access the
number of iterations, so that isn't possible at the moment (unless I'm missing
it?). Can we add a TODO that when (if?) we add total iterations to the KMeans
model summary we can change this test?
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