org.apache.spark.mllib.clustering

Class KMeansModel

java.lang.Object

org.apache.spark.mllib.clustering.KMeansModel

All Implemented Interfaces:

java.io.Serializable, PMMLExportable, Saveable

Direct Known Subclasses:

StreamingKMeansModel

public class KMeansModel
extends java.lang.Object
implements Saveable, scala.Serializable, PMMLExportable

A clustering model for K-means. Each point belongs to the cluster with the closest center.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
KMeansModel(java.lang.Iterable<Vector> centers) A Java-friendly constructor that takes an Iterable of Vectors.
KMeansModel(Vector[] clusterCenters)

Method Summary

Methods

Modifier and Type	Method and Description
Vector[]	clusterCenters()
double	computeCost(RDD<Vector> data) Return the K-means cost (sum of squared distances of points to their nearest center) for this model on the given data.
protected java.lang.String	formatVersion() Current version of model save/load format.
int	k() Total number of clusters.
static KMeansModel	load(SparkContext sc, java.lang.String path)
JavaRDD<java.lang.Integer>	predict(JavaRDD<Vector> points) Maps given points to their cluster indices.
RDD<java.lang.Object>	predict(RDD<Vector> points) Maps given points to their cluster indices.
int	predict(Vector point) Returns the cluster index that a given point belongs to.
void	save(SparkContext sc, java.lang.String path) Save this model to the given path.

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.apache.spark.mllib.pmml.PMMLExportable

toPMML, toPMML, toPMML, toPMML, toPMML

Constructor Detail

KMeansModel

public KMeansModel(Vector[] clusterCenters)

KMeansModel

public KMeansModel(java.lang.Iterable<Vector> centers)

A Java-friendly constructor that takes an Iterable of Vectors.

Parameters:

centers - (undocumented)

Method Detail

load

public static KMeansModel load(SparkContext sc,
               java.lang.String path)

clusterCenters

public Vector[] clusterCenters()

k

public int k()

Total number of clusters.

Returns:

(undocumented)

predict

public int predict(Vector point)

Returns the cluster index that a given point belongs to.

Parameters:

point - (undocumented)

Returns:

(undocumented)

predict

public RDD<java.lang.Object> predict(RDD<Vector> points)

Maps given points to their cluster indices.

Parameters:

points - (undocumented)

Returns:

(undocumented)

predict

public JavaRDD<java.lang.Integer> predict(JavaRDD<Vector> points)

Maps given points to their cluster indices.

Parameters:

points - (undocumented)

Returns:

(undocumented)

computeCost

public double computeCost(RDD<Vector> data)

Return the K-means cost (sum of squared distances of points to their nearest center) for this model on the given data.

Parameters:

data - (undocumented)

Returns:

(undocumented)

save

public void save(SparkContext sc,
        java.lang.String path)

Description copied from interface: Saveable

Save this model to the given path.

This saves: - human-readable (JSON) model metadata to path/metadata/ - Parquet formatted data to path/data/

The model may be loaded using Loader.load.

Specified by:

save in interface Saveable

Parameters:

sc - Spark context used to save model data.

path - Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.

formatVersion

protected java.lang.String formatVersion()

Description copied from interface: Saveable

Current version of model save/load format.

Specified by:

formatVersion in interface Saveable