Class/Object

org.apache.spark.mllib.fpm

PrefixSpan

Related Docs: object PrefixSpan | package fpm

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class PrefixSpan extends Logging with Serializable

A parallel PrefixSpan algorithm to mine frequent sequential patterns. The PrefixSpan algorithm is described in J. Pei, et al., PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth (see here).

Annotations
@Since( "1.5.0" )
Source
PrefixSpan.scala
See also

Sequential Pattern Mining (Wikipedia)

Linear Supertypes
Serializable, Serializable, Logging, AnyRef, Any
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Inherited
  1. PrefixSpan
  2. Serializable
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  4. Logging
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Visibility
  1. Public
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Instance Constructors

  1. new PrefixSpan()

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    Constructs a default instance with default parameters {minSupport: 0.1, maxPatternLength: 10, maxLocalProjDBSize: 32000000L}.

    Constructs a default instance with default parameters {minSupport: 0.1, maxPatternLength: 10, maxLocalProjDBSize: 32000000L}.

    Annotations
    @Since( "1.5.0" )

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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    protected[java.lang]
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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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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

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  10. def getMaxLocalProjDBSize: Long

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    Gets the maximum number of items allowed in a projected database before local processing.

    Gets the maximum number of items allowed in a projected database before local processing.

    Annotations
    @Since( "1.5.0" )
  11. def getMaxPatternLength: Int

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    Gets the maximal pattern length (i.e.

    Gets the maximal pattern length (i.e. the length of the longest sequential pattern to consider.

    Annotations
    @Since( "1.5.0" )
  12. def getMinSupport: Double

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    Get the minimal support (i.e.

    Get the minimal support (i.e. the frequency of occurrence before a pattern is considered frequent).

    Annotations
    @Since( "1.5.0" )
  13. def hashCode(): Int

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

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    protected
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    Logging
  15. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Logging
  16. final def isInstanceOf[T0]: Boolean

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  17. def isTraceEnabled(): Boolean

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    protected
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    Logging
  18. def log: Logger

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

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

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

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

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

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

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    Logging
  25. def logName: String

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

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

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

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

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

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  31. final def notify(): Unit

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  32. final def notifyAll(): Unit

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  33. def run[Item, Itemset <: Iterable[Item], Sequence <: Iterable[Itemset]](data: JavaRDD[Sequence]): PrefixSpanModel[Item]

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    A Java-friendly version of run() that reads sequences from a JavaRDD and returns frequent sequences in a PrefixSpanModel.

    A Java-friendly version of run() that reads sequences from a JavaRDD and returns frequent sequences in a PrefixSpanModel.

    Item

    item type

    Itemset

    itemset type, which is an Iterable of Items

    Sequence

    sequence type, which is an Iterable of Itemsets

    data

    ordered sequences of itemsets stored as Java Iterable of Iterables

    returns

    a PrefixSpanModel that contains the frequent sequential patterns

    Annotations
    @Since( "1.5.0" )
  34. def run[Item](data: RDD[Array[Array[Item]]])(implicit arg0: ClassTag[Item]): PrefixSpanModel[Item]

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    Finds the complete set of frequent sequential patterns in the input sequences of itemsets.

    Finds the complete set of frequent sequential patterns in the input sequences of itemsets.

    data

    sequences of itemsets.

    returns

    a PrefixSpanModel that contains the frequent patterns

    Annotations
    @Since( "1.5.0" )
  35. def setMaxLocalProjDBSize(maxLocalProjDBSize: Long): PrefixSpan.this.type

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    Sets the maximum number of items (including delimiters used in the internal storage format) allowed in a projected database before local processing (default: 32000000L).

    Sets the maximum number of items (including delimiters used in the internal storage format) allowed in a projected database before local processing (default: 32000000L).

    Annotations
    @Since( "1.5.0" )
  36. def setMaxPatternLength(maxPatternLength: Int): PrefixSpan.this.type

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    Sets maximal pattern length (default: 10).

    Sets maximal pattern length (default: 10).

    Annotations
    @Since( "1.5.0" )
  37. def setMinSupport(minSupport: Double): PrefixSpan.this.type

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    Sets the minimal support level (default: 0.1).

    Sets the minimal support level (default: 0.1).

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

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  39. def toString(): String

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  40. final def wait(): Unit

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

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  42. 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

Ungrouped