Class BisectingKMeansSummary

All Implemented Interfaces:
Serializable, scala.Serializable

public class BisectingKMeansSummary extends ClusteringSummary
Summary of BisectingKMeans.

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.

See Also:
  • Method Details

    • trainingCost

      public double trainingCost()