KMeansModel

Value Members

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

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

   Definition Classes

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

   

   Definition Classes

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4. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

5. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

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   Annotations

   @throws( ... )

6. val clusterCenters: Array[Vector]

   

   Annotations

   @Since( "1.0.0" )

7. 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" )

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

   

   Definition Classes

   AnyRef

9. def equals(arg0: Any): Boolean

   

   Definition Classes

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10. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

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    Annotations

    @throws( classOf[java.lang.Throwable] )

11. def formatVersion: String

    

    Current version of model save/load format.

    Current version of model save/load format.

    Attributes

    protected

    Definition Classes

    KMeansModel → Saveable

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

    

    Definition Classes

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13. def hashCode(): Int

    

    Definition Classes

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14. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

15. def k: Int

    

    Total number of clusters.

    Total number of clusters.

    Annotations

    @Since( "0.8.0" )

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

    

    Definition Classes

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17. final def notify(): Unit

    

    Definition Classes

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18. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

19. 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" )

20. 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" )

21. 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" )

22. 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" )

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

    

    Definition Classes

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24. 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" )

25. 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" )

26. 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" )

27. 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" )

28. def toString(): String

    

    Definition Classes

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29. final def wait(): Unit

    

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    @throws( ... )

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

    

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    @throws( ... )

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

    

    Definition Classes

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    @throws( ... )