org.apache.spark.mllib.clustering

BisectingKMeansModel

class BisectingKMeansModel extends Serializable with 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.

Annotations
@Since( "1.6.0" ) @Experimental()
Source
BisectingKMeansModel.scala
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  1. final def !=(arg0: AnyRef): Boolean

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

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  3. final def ##(): Int

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

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  8. def clusterCenters: Array[Vector]

    Leaf cluster centers.

    Leaf cluster centers.

    Annotations
    @Since( "1.6.0" )
  9. def computeCost(data: JavaRDD[Vector]): Double

    Java-friendly version of computeCost().

    Java-friendly version of computeCost().

    Annotations
    @Since( "1.6.0" )
  10. def computeCost(data: RDD[Vector]): Double

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

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

    Annotations
    @Since( "1.6.0" )
  11. def computeCost(point: Vector): Double

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

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

    Annotations
    @Since( "1.6.0" )
  12. final def eq(arg0: AnyRef): Boolean

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  13. def equals(arg0: Any): Boolean

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  14. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  15. final def getClass(): Class[_]

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  16. def hashCode(): Int

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  17. final def isInstanceOf[T0]: Boolean

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  18. def isTraceEnabled(): Boolean

    Attributes
    protected
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    Logging
  19. lazy val k: Int

    Number of leaf clusters.

  20. def log: Logger

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  21. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  22. def logDebug(msg: ⇒ String): Unit

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  23. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  24. def logError(msg: ⇒ String): Unit

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  25. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  26. def logInfo(msg: ⇒ String): Unit

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  27. def logName: String

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  28. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  29. def logTrace(msg: ⇒ String): Unit

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  30. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  31. def logWarning(msg: ⇒ String): Unit

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

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  33. final def notify(): Unit

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  34. final def notifyAll(): Unit

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

    Java-friendly version of predict().

    Java-friendly version of predict().

    Annotations
    @Since( "1.6.0" )
  36. def predict(points: RDD[Vector]): RDD[Int]

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

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

    Annotations
    @Since( "1.6.0" )
  37. def predict(point: Vector): Int

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

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

    Annotations
    @Since( "1.6.0" )
  38. final def synchronized[T0](arg0: ⇒ T0): T0

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  39. def toString(): String

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  40. final def wait(): Unit

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

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

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