Spark K-Means通过归一化获得原始簇中心/质心

val kmeans = new KMeans().setK(k).setSeed(1L)
val model = kmeans.fit(train_dataset)

然后提取聚类中心(质心)

 var clusterCenters:Seq[(Double,Double,Double,Double,Double,Double,Double,Double,Double)] = Seq()
for(e <- model.clusterCenters){
  clusterCenters = clusterCenters :+ ((e(0)),e(1),e(2),e(3),e(4),e(5),e(6),e(7),e(8))
}

import sc.implicits._
var centroidsDF = clusterCenters.toDF()

现在我有一个问题,我已经规范化了数据之前,以改善聚类结果。

 val scaler = new StandardScaler()
      .setInputCol("features")
      .setOutputCol("scaledFeatures")
      .setWithStd(true)
      .setWithMean(false)
    scalerModel = scaler.fit(train_dataset)
    scaledData = scalerModel.transform(train_dataset)