Class/Object

org.apache.spark.mllib.fpm

FPGrowth

Related Docs: object FPGrowth | package fpm

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class FPGrowth extends Logging with Serializable

A parallel FP-growth algorithm to mine frequent itemsets. The algorithm is described in Li et al., PFP: Parallel FP-Growth for Query Recommendation. PFP distributes computation in such a way that each worker executes an independent group of mining tasks. The FP-Growth algorithm is described in Han et al., Mining frequent patterns without candidate generation.

Annotations
@Since( "1.3.0" )
Source
FPGrowth.scala
See also

Association rule learning (Wikipedia)

Linear Supertypes
Serializable, Serializable, Logging, AnyRef, Any
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  1. FPGrowth
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Visibility
  1. Public
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Instance Constructors

  1. new FPGrowth()

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    Constructs a default instance with default parameters {minSupport: 0.3, numPartitions: same as the input data}.

    Constructs a default instance with default parameters {minSupport: 0.3, numPartitions: same as the input data}.

    Annotations
    @Since( "1.3.0" )

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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    @throws( ... )

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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

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  10. def hashCode(): Int

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  11. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    protected
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    Logging

  12. final def isInstanceOf[T0]: Boolean

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  13. def isTraceEnabled(): Boolean

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  14. def log: Logger

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

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

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

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

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

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

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  21. def logName: String

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

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

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

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

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

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  27. final def notify(): Unit

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  28. final def notifyAll(): Unit

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  29. def run[Item, Basket <: Iterable[Item]](data: JavaRDD[Basket]): FPGrowthModel[Item]

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    Java-friendly version of run.

    Java-friendly version of run.

    Annotations
    @Since( "1.3.0" )

  30. def run[Item](data: RDD[Array[Item]])(implicit arg0: ClassTag[Item]): FPGrowthModel[Item]

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    Computes an FP-Growth model that contains frequent itemsets.

    Computes an FP-Growth model that contains frequent itemsets.

    data

    input data set, each element contains a transaction

    returns

    an FPGrowthModel

    Annotations
    @Since( "1.3.0" )

  31. def setMinSupport(minSupport: Double): FPGrowth.this.type

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    Sets the minimal support level (default: 0.3).

    Sets the minimal support level (default: 0.3).

    Annotations
    @Since( "1.3.0" )

  32. def setNumPartitions(numPartitions: Int): FPGrowth.this.type

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    Sets the number of partitions used by parallel FP-growth (default: same as input data).

    Sets the number of partitions used by parallel FP-growth (default: same as input data).

    Annotations
    @Since( "1.3.0" )

  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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    @throws( ... )

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

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    @throws( ... )

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

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Inherited from Serializable

Inherited from Serializable

Inherited from Logging

Inherited from AnyRef

Inherited from Any

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