org.apache.spark.mllib.clustering

Class BisectingKMeansModel

Object

org.apache.spark.mllib.clustering.BisectingKMeansModel

All Implemented Interfaces:

java.io.Serializable, Logging

public class BisectingKMeansModel
extends Object
implements scala.Serializable, Logging

Clustering model produced by BisectingKMeans. The prediction is done level-by-level from the root node to a leaf node, and at each node among its children the closest to the input point is selected.

param: root the root node of the clustering tree

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
Vector[]	clusterCenters() Leaf cluster centers.
double	computeCost(JavaRDD<Vector> data) Java-friendly version of computeCost().
double	computeCost(RDD<Vector> data) Computes the sum of squared distances between the input points and their corresponding cluster centers.
double	computeCost(Vector point) Computes the squared distance between the input point and the cluster center it belongs to.
int	k() Number of leaf clusters.
JavaRDD<Integer>	predict(JavaRDD<Vector> points) Java-friendly version of predict().
RDD<Object>	predict(RDD<Vector> points) Predicts the indices of the clusters that the input points belong to.
int	predict(Vector point) Predicts the index of the cluster that the input point belongs to.
org.apache.spark.mllib.clustering.ClusteringTreeNode	root()

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Method Detail

root

public org.apache.spark.mllib.clustering.ClusteringTreeNode root()

clusterCenters

public Vector[] clusterCenters()

Leaf cluster centers.

Returns:

(undocumented)

k

public int k()

Number of leaf clusters.

Returns:

(undocumented)

predict

public int predict(Vector point)

Predicts the index of the cluster that the input point belongs to.

Parameters:

point - (undocumented)

Returns:

(undocumented)

predict

public RDD<Object> predict(RDD<Vector> points)

Predicts the indices of the clusters that the input points belong to.

Parameters:

points - (undocumented)

Returns:

(undocumented)

predict

public JavaRDD<Integer> predict(JavaRDD<Vector> points)

Java-friendly version of predict().

Parameters:

points - (undocumented)

Returns:

(undocumented)

computeCost

public double computeCost(Vector point)

Computes the squared distance between the input point and the cluster center it belongs to.

Parameters:

point - (undocumented)

Returns:

(undocumented)

computeCost

public double computeCost(RDD<Vector> data)

Computes the sum of squared distances between the input points and their corresponding cluster centers.

Parameters:

data - (undocumented)

Returns:

(undocumented)

computeCost

public double computeCost(JavaRDD<Vector> data)

Java-friendly version of computeCost().

Parameters:

data - (undocumented)

Returns:

(undocumented)