Package org.apache.spark.ml.clustering

Class BisectingKMeansSummary

Object

org.apache.spark.ml.clustering.ClusteringSummary

org.apache.spark.ml.clustering.BisectingKMeansSummary

All Implemented Interfaces:

Serializable, Summary

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:

• Serialized Form

Method Summary

Modifier and Type	Method	Description
double	trainingCost()

Methods inherited from class org.apache.spark.ml.clustering.ClusteringSummary

cluster, clusterSizes, featuresCol, k, numIter, predictionCol, predictions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

trainingCost

public double trainingCost()