public class BisectingKMeansSummary extends ClusteringSummary
 param:  predictions  DataFrame produced by BisectingKMeansModel.transform().
 param:  predictionCol  Name for column of predicted clusters in predictions.
 param:  featuresCol  Name for column of features in predictions.
 param:  k  Number of clusters.
 param:  numIter  Number of iterations.
 param:  trainingCost Sum of the cost to the nearest centroid for all points in the training
                     dataset. This is equivalent to sklearn's inertia.
| Modifier and Type | Method and Description | 
|---|---|
| double | trainingCost() | 
cluster, clusterSizes, featuresCol, k, numIter, predictionCol, predictions