Packages

c

org.apache.spark.ml.clustering

ClusteringSummary

class ClusteringSummary extends Serializable

Summary of clustering algorithms.

Linear Supertypes
Serializable, Serializable, AnyRef, Any
Known Subclasses
BisectingKMeansSummary, GaussianMixtureSummary, KMeansSummary
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  1. final def !=(arg0: Any): Boolean
    Definition Classes
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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
    Attributes
    protected[lang]
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    Annotations
    @throws( ... ) @native()
  6. lazy val cluster: DataFrame

    Cluster centers of the transformed data.

    Cluster centers of the transformed data.

    Annotations
    @transient()
  7. lazy val clusterSizes: Array[Long]

    Size of (number of data points in) each cluster.

  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
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  9. def equals(arg0: Any): Boolean
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  10. val featuresCol: String
  11. def finalize(): Unit
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  12. final def getClass(): Class[_]
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  13. def hashCode(): Int
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  14. final def isInstanceOf[T0]: Boolean
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  15. val k: Int
  16. final def ne(arg0: AnyRef): Boolean
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  17. final def notify(): Unit
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    @native()
  18. final def notifyAll(): Unit
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    @native()
  19. val numIter: Int
    Annotations
    @Since( "2.4.0" )
  20. val predictionCol: String
  21. val predictions: DataFrame
  22. final def synchronized[T0](arg0: ⇒ T0): T0
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  23. def toString(): String
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  24. final def wait(): Unit
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  25. final def wait(arg0: Long, arg1: Int): Unit
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  26. final def wait(arg0: Long): Unit
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