org.apache.spark.mllib.clustering

KMeansModel

class KMeansModel extends Saveable with Serializable with PMMLExportable

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

Annotations
@Since( "0.8.0" )
Linear Supertypes
PMMLExportable, Serializable, Serializable, Saveable, AnyRef, Any
Known Subclasses
StreamingKMeansModel
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. KMeansModel
  2. PMMLExportable
  3. Serializable
  4. Serializable
  5. Saveable
  6. AnyRef
  7. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new KMeansModel(centers: Iterable[Vector])

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

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

    Annotations
    @Since( "1.4.0" )

  2. new KMeansModel(clusterCenters: Array[Vector])

    Annotations
    @Since( "1.1.0" )

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  8. val clusterCenters: Array[Vector]

    Annotations
    @Since( "1.0.0" )

  9. def computeCost(data: RDD[Vector]): Double

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

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

    Annotations
    @Since( "0.8.0" )

  10. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  12. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  13. def formatVersion: String

    Current version of model save/load format.

    Current version of model save/load format.

    Attributes
    protected
    Definition Classes
    KMeansModel → Saveable

  14. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  15. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  16. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  17. def k: Int

    Total number of clusters.

    Total number of clusters.

    Annotations
    @Since( "0.8.0" )

  18. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  19. final def notify(): Unit

    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  21. def predict(points: JavaRDD[Vector]): JavaRDD[Integer]

    Maps given points to their cluster indices.

    Maps given points to their cluster indices.

    Annotations
    @Since( "1.0.0" )

  22. def predict(points: RDD[Vector]): RDD[Int]

    Maps given points to their cluster indices.

    Maps given points to their cluster indices.

    Annotations
    @Since( "1.0.0" )

  23. def predict(point: Vector): Int

    Returns the cluster index that a given point belongs to.

    Returns the cluster index that a given point belongs to.

    Annotations
    @Since( "0.8.0" )

  24. def save(sc: SparkContext, path: String): Unit

    Save this model to the given path.

    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.

    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.

    Definition Classes
    KMeansModel → Saveable
    Annotations
    @Since( "1.4.0" )

  25. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  26. def toPMML(): String

    :: Experimental :: Export the model to a String in PMML format

    :: Experimental :: Export the model to a String in PMML format

    Definition Classes
    PMMLExportable
    Annotations
    @Experimental() @Since( "1.4.0" )

  27. def toPMML(outputStream: OutputStream): Unit

    :: Experimental :: Export the model to the OutputStream in PMML format

    :: Experimental :: Export the model to the OutputStream in PMML format

    Definition Classes
    PMMLExportable
    Annotations
    @Experimental() @Since( "1.4.0" )

  28. def toPMML(sc: SparkContext, path: String): Unit

    :: Experimental :: Export the model to a directory on a distributed file system in PMML format

    :: Experimental :: Export the model to a directory on a distributed file system in PMML format

    Definition Classes
    PMMLExportable
    Annotations
    @Experimental() @Since( "1.4.0" )

  29. def toPMML(localPath: String): Unit

    :: Experimental :: Export the model to a local file in PMML format

    :: Experimental :: Export the model to a local file in PMML format

    Definition Classes
    PMMLExportable
    Annotations
    @Experimental() @Since( "1.4.0" )

  30. def toString(): String

    Definition Classes
    AnyRef → Any

  31. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  32. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  33. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from PMMLExportable

Inherited from Serializable

Inherited from Serializable

Inherited from Saveable

Inherited from AnyRef

Inherited from Any

Ungrouped