Class/Object

org.apache.spark.mllib.clustering

BisectingKMeansModel

Related Docs: object BisectingKMeansModel | package clustering

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class BisectingKMeansModel extends Serializable with Saveable 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" )
Linear Supertypes
Logging, Saveable, Serializable, Serializable, AnyRef, Any
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  1. BisectingKMeansModel
  2. Logging
  3. Saveable
  4. Serializable
  5. Serializable
  6. AnyRef
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Value Members

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

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  2. final def ##(): Int

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

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    AnyRef
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    @throws( ... )
  6. def clusterCenters: Array[Vector]

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    Leaf cluster centers.

    Leaf cluster centers.

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

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    Java-friendly version of computeCost().

    Java-friendly version of computeCost().

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

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    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" )
  9. def computeCost(point: Vector): Double

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

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    AnyRef
  11. def equals(arg0: Any): Boolean

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  12. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  13. def formatVersion: String

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    Current version of model save/load format.

    Current version of model save/load format.

    Attributes
    protected
    Definition Classes
    BisectingKMeansModelSaveable
  14. final def getClass(): Class[_]

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  15. def hashCode(): Int

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  16. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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    Attributes
    protected
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    Logging
  17. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Logging
  18. final def isInstanceOf[T0]: Boolean

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  19. def isTraceEnabled(): Boolean

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    protected
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    Logging
  20. lazy val k: Int

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    Number of leaf clusters.

  21. def log: Logger

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

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    Logging
  23. def logDebug(msg: ⇒ String): Unit

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

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    Logging
  25. def logError(msg: ⇒ String): Unit

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

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    Logging
  27. def logInfo(msg: ⇒ String): Unit

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    Logging
  28. def logName: String

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

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    Logging
  30. def logTrace(msg: ⇒ String): Unit

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

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    Logging
  32. def logWarning(msg: ⇒ String): Unit

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    Logging
  33. final def ne(arg0: AnyRef): Boolean

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  34. final def notify(): Unit

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  35. final def notifyAll(): Unit

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

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    Java-friendly version of predict().

    Java-friendly version of predict().

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

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    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" )
  38. def predict(point: Vector): Int

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

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    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
    BisectingKMeansModelSaveable
    Annotations
    @Since( "2.0.0" )
  40. final def synchronized[T0](arg0: ⇒ T0): T0

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  41. def toString(): String

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  42. final def wait(): Unit

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    @throws( ... )
  43. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  44. final def wait(arg0: Long): Unit

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Inherited from Logging

Inherited from Saveable

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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