Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/11119#discussion_r52282898
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala ---
@@ -106,6 +106,38 @@ 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 points = Array(
+ Vectors.dense(0.0, 0.0, 0.0),
+ Vectors.dense(1.0, 1.0, 1.0),
+ Vectors.dense(2.0, 2.0, 2.0),
+ Vectors.dense(3.0, 3.0, 3.0),
+ Vectors.dense(4.0, 4.0, 4.0)
+ )
+
+ // creating an initial model
+ val initialModel = new KMeansModel("test model", new
MLlibKMeansModel(points))
+
+ val predictionColName = "kmeans_prediction"
+ val kmeans = new KMeans()
+ .setK(k)
+ .setPredictionCol(predictionColName)
+ .setSeed(1)
+ .setInitialModel(initialModel)
+ val model = kmeans.fit(dataset)
+ assert(model.clusterCenters.length === k)
+
--- End diff --
Maybe we can train a model here, and use it as initalModel. Since it's
already converged, you should see that the next training will take only 1
iteration to converge.
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