FPGrowth (Spark 3.5.5 JavaDoc) (original) (raw)

• Object

• • org.apache.spark.mllib.fpm.FPGrowth

• All Implemented Interfaces:
  java.io.Serializable, org.apache.spark.internal.Logging

public class FPGrowth
extends Object
implements org.apache.spark.internal.Logging, scala.Serializable
See Also:
Association rule learning (Wikipedia)
, Serialized Form

• • Nested Class Summary

  Nested Classes

  Modifier and Type	Class and Description
  static class	FPGrowth.FreqItemset<Item> Frequent itemset.

     * ### Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging  
     `org.apache.spark.internal.Logging.SparkShellLoggingFilter`  

  • Constructor Summary

  Constructors

  Constructor and Description
  FPGrowth() Constructs a default instance with default parameters {minSupport: 0.3, numPartitions: same as the input data}.

  • Method Summary

  All Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  <Item,Basket extends Iterable>FPGrowthModel	run(JavaRDD data) Java-friendly version of run.
  FPGrowthModel	run(RDD data, scala.reflect.ClassTag evidence$4) Computes an FP-Growth model that contains frequent itemsets.
  FPGrowth	setMinSupport(double minSupport) Sets the minimal support level (default: 0.3).
  FPGrowth	setNumPartitions(int numPartitions) Sets the number of partitions used by parallel FP-growth (default: same as input data).

     * ### Methods inherited from class Object  
     `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`  
     * ### Methods inherited from interface org.apache.spark.internal.Logging  
     `$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize`

• • Constructor Detail

     * #### FPGrowth  
     public FPGrowth()  
     Constructs a default instance with default parameters {minSupport: `0.3`, numPartitions: same as the input data}.  

  • Method Detail

    * #### setMinSupport  
    public [FPGrowth](../../../../../org/apache/spark/mllib/fpm/FPGrowth.html "class in org.apache.spark.mllib.fpm") setMinSupport(double minSupport)  
    Sets the minimal support level (default: `0.3`).  
    Parameters:  
    `minSupport` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### setNumPartitions  
    public [FPGrowth](../../../../../org/apache/spark/mllib/fpm/FPGrowth.html "class in org.apache.spark.mllib.fpm") setNumPartitions(int numPartitions)  
    Sets the number of partitions used by parallel FP-growth (default: same as input data).  
    Parameters:  
    `numPartitions` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### run  
    public <Item> [FPGrowthModel](../../../../../org/apache/spark/mllib/fpm/FPGrowthModel.html "class in org.apache.spark.mllib.fpm")<Item> run([RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<Object> data,  
                                          scala.reflect.ClassTag<Item> evidence$4)  
    Computes an FP-Growth model that contains frequent itemsets.  
    Parameters:  
    `data` \- input data set, each element contains a transaction  
    `evidence$4` \- (undocumented)  
    Returns:  
    an [FPGrowthModel](../../../../../org/apache/spark/mllib/fpm/FPGrowthModel.html "class in org.apache.spark.mllib.fpm")  
    * #### run  
    public <Item,Basket extends Iterable<Item>> [FPGrowthModel](../../../../../org/apache/spark/mllib/fpm/FPGrowthModel.html "class in org.apache.spark.mllib.fpm")<Item> run([JavaRDD](../../../../../org/apache/spark/api/java/JavaRDD.html "class in org.apache.spark.api.java")<Basket> data)  
    Java-friendly version of `run`.  
    Parameters:  
    `data` \- (undocumented)  
    Returns:  
    (undocumented)