Experimental

org.apache.spark.ml.clustering

Class ClusteringSummary

Object

org.apache.spark.ml.clustering.ClusteringSummary

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

BisectingKMeansSummary, GaussianMixtureSummary, KMeansSummary

public class ClusteringSummary
extends Object
implements scala.Serializable

Summary of clustering algorithms.

param: predictions DataFrame produced by model.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.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
Dataset<Row>	cluster() Cluster centers of the transformed data.
long[]	clusterSizes() Size of (number of data points in) each cluster.
String	featuresCol()
int	k()
int	numIter()
String	predictionCol()
Dataset<Row>	predictions()

Methods inherited from class Object

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

Method Detail

cluster

public Dataset<Row> cluster()

Cluster centers of the transformed data.

Returns:

(undocumented)

clusterSizes

public long[] clusterSizes()

Size of (number of data points in) each cluster.

Returns:

(undocumented)

featuresCol

public String featuresCol()

k

public int k()

numIter

public int numIter()

predictionCol

public String predictionCol()

predictions

public Dataset<Row> predictions()