org.apache.spark.mllib.fpm

AssociationRules

class AssociationRules extends Logging with Serializable

:: Experimental ::

Generates association rules from a RDD[FreqItemset[Item]. This method only generates association rules which have a single item as the consequent.

Annotations
@Since( "1.5.0" ) @Experimental()
Source
AssociationRules.scala
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Instance Constructors

  1. new AssociationRules()

    Constructs a default instance with default parameters {minConfidence = 0.

    Constructs a default instance with default parameters {minConfidence = 0.8}.

    Annotations
    @Since( "1.5.0" )

Value Members

  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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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. def isTraceEnabled(): Boolean

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  15. def log: Logger

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

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

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

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

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

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

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  22. def logName: String

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

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

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

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

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

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  28. final def notify(): Unit

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  29. final def notifyAll(): Unit

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  30. def run[Item](freqItemsets: JavaRDD[FreqItemset[Item]]): JavaRDD[Rule[Item]]

    Java-friendly version of run.

    Java-friendly version of run.

    Annotations
    @Since( "1.5.0" )
  31. def run[Item](freqItemsets: RDD[FreqItemset[Item]])(implicit arg0: ClassTag[Item]): RDD[Rule[Item]]

    Computes the association rules with confidence above minConfidence.

    Computes the association rules with confidence above minConfidence.

    freqItemsets

    frequent itemset model obtained from FPGrowth

    returns

    a Set[Rule[Item] containing the assocation rules.

    Annotations
    @Since( "1.5.0" )
  32. def setMinConfidence(minConfidence: Double): AssociationRules.this.type

    Sets the minimal confidence (default: 0.8).

    Sets the minimal confidence (default: 0.8).

    Annotations
    @Since( "1.5.0" )
  33. final def synchronized[T0](arg0: ⇒ T0): T0

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  34. def toString(): String

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  35. final def wait(): Unit

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

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

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Inherited from Serializable

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