Class

org.apache.spark.ml.clustering

GaussianMixtureSummary

Related Doc: package clustering

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class GaussianMixtureSummary extends ClusteringSummary

:: Experimental :: Summary of GaussianMixture.

Annotations
@Since( "2.0.0" ) @Experimental()
Source
GaussianMixture.scala
Linear Supertypes
ClusteringSummary, Serializable, Serializable, AnyRef, Any
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  1. GaussianMixtureSummary
  2. ClusteringSummary
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  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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    @throws( ... )

  6. lazy val cluster: DataFrame

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    Cluster centers of the transformed data.

    Cluster centers of the transformed data.

    Definition Classes
    ClusteringSummary

  7. lazy val clusterSizes: Array[Long]

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

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

    Definition Classes
    ClusteringSummary

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

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  9. def equals(arg0: Any): Boolean

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  10. val featuresCol: String

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    Name for column of features in predictions.

    Name for column of features in predictions.

    Definition Classes
    ClusteringSummary

  11. def finalize(): Unit

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

  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

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    Number of clusters.

    Number of clusters.

    Definition Classes
    ClusteringSummary

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. val predictionCol: String

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    Name for column of predicted clusters in predictions.

    Name for column of predicted clusters in predictions.

    Definition Classes
    ClusteringSummary

  20. val predictions: DataFrame

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    DataFrame produced by model.transform().

    DataFrame produced by model.transform().

    Definition Classes
    ClusteringSummary

  21. lazy val probability: DataFrame

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    Probability of each cluster.

    Probability of each cluster.

    Annotations
    @Since( "2.0.0" )

  22. val probabilityCol: String

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    Name for column of predicted probability of each cluster in predictions.

    Name for column of predicted probability of each cluster in predictions.

    Annotations
    @Since( "2.0.0" )

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

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  24. def toString(): String

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  25. final def wait(): Unit

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

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

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Inherited from ClusteringSummary

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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