Github user dbtsai commented on a diff in the pull request: https://github.com/apache/spark/pull/11119#discussion_r82105944 --- Diff: mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala --- @@ -137,18 +142,53 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultR assert(model.clusterCenters === model2.clusterCenters) } val kmeans = new KMeans() - testEstimatorAndModelReadWrite(kmeans, dataset, KMeansSuite.allParamSettings, checkModelData) + testEstimatorAndModelReadWrite(kmeans, dataset, KMeansSuite.allParamSettings, checkModelData, + Map("initialModel" -> (checkModelData _).asInstanceOf[(Any, Any) => Unit])) + } + + test("Initialize using given cluster centers") { + val kmeans = new KMeans().setK(k).setSeed(1).setMaxIter(1) + val oneIterModel = kmeans.fit(dataset) + val twoIterModel = kmeans.copy(ParamMap(ParamPair(kmeans.maxIter, 2))).fit(dataset) + val oneMoreIterModel = kmeans.setInitialModel(oneIterModel).fit(dataset) + + twoIterModel.clusterCenters.zip(oneMoreIterModel.clusterCenters) + .foreach { case (center1, center2) => assert(center1 ~== center2 absTol 1E-8) } + } + + test("Initialize using wrong model") { + val kmeans = new KMeans().setK(k).setSeed(1).setMaxIter(10) + + val wrongKModel = KMeansSuite.generateRandomKMeansModel(3, k + 1) + val wrongKModelThrown = intercept[IllegalArgumentException] { + kmeans.setInitialModel(wrongKModel).fit(dataset) + } + assert(wrongKModelThrown.getMessage.contains("mismatched cluster count")) + + val wrongDimModel = KMeansSuite.generateRandomKMeansModel(4, k) + val wrongDimModelThrown = intercept[IllegalArgumentException] { + kmeans.setInitialModel(wrongDimModel).fit(dataset) + } + assert(wrongDimModelThrown.getMessage.contains("mismatched dimension")) } } --- End diff -- Let's have a test case that without explicitly setting k, k can be inferred from initial model.
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