AssociationRules (Spark 3.5.5 JavaDoc) (original) (raw)

• Object

• • org.apache.spark.mllib.fpm.AssociationRules

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

public class AssociationRules
extends Object
implements org.apache.spark.internal.Logging, scala.Serializable
Generates association rules from a RDD[FreqItemset[Item}. This method only generates association rules which have a single item as the consequent.
See Also:
Serialized Form

• • Nested Class Summary

  Nested Classes

  Modifier and Type	Class and Description
  static class	AssociationRules.Rule<Item> An association rule between sets of items.

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

  • Constructor Summary

  Constructors

  Constructor and Description
  AssociationRules() Constructs a default instance with default parameters {minConfidence = 0.8}.

  • Method Summary

  All Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  JavaRDD<AssociationRules.Rule>	run(JavaRDD<FPGrowth.FreqItemset> freqItemsets) Java-friendly version of run.
  RDD<AssociationRules.Rule>	run(RDD<FPGrowth.FreqItemset> freqItemsets, scala.reflect.ClassTag evidence$1) Computes the association rules with confidence above minConfidence.
  RDD<AssociationRules.Rule>	run(RDD<FPGrowth.FreqItemset> freqItemsets, scala.collection.Map<Item,Object> itemSupport, scala.reflect.ClassTag evidence$2) Computes the association rules with confidence above minConfidence.
  AssociationRules	setMinConfidence(double minConfidence) Sets the minimal confidence (default: 0.8).

     * ### 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

     * #### AssociationRules  
     public AssociationRules()  
     Constructs a default instance with default parameters {minConfidence = 0.8}.  

  • Method Detail

    * #### setMinConfidence  
    public [AssociationRules](../../../../../org/apache/spark/mllib/fpm/AssociationRules.html "class in org.apache.spark.mllib.fpm") setMinConfidence(double minConfidence)  
    Sets the minimal confidence (default: `0.8`).  
    Parameters:  
    `minConfidence` \- (undocumented)  
    Returns:  
    (undocumented)  
    * #### run  
    public <Item> [RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[AssociationRules.Rule](../../../../../org/apache/spark/mllib/fpm/AssociationRules.Rule.html "class in org.apache.spark.mllib.fpm")<Item>> run([RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[FPGrowth.FreqItemset](../../../../../org/apache/spark/mllib/fpm/FPGrowth.FreqItemset.html "class in org.apache.spark.mllib.fpm")<Item>> freqItemsets,  
                                                       scala.reflect.ClassTag<Item> evidence$1)  
    Computes the association rules with confidence above `minConfidence`.  
    Parameters:  
    `freqItemsets` \- frequent itemset model obtained from [FPGrowth](../../../../../org/apache/spark/mllib/fpm/FPGrowth.html "class in org.apache.spark.mllib.fpm")  
    `evidence$1` \- (undocumented)  
    Returns:  
    a `RDD[Rule[Item}` containing the association rules.  
    * #### run  
    public <Item> [RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[AssociationRules.Rule](../../../../../org/apache/spark/mllib/fpm/AssociationRules.Rule.html "class in org.apache.spark.mllib.fpm")<Item>> run([RDD](../../../../../org/apache/spark/rdd/RDD.html "class in org.apache.spark.rdd")<[FPGrowth.FreqItemset](../../../../../org/apache/spark/mllib/fpm/FPGrowth.FreqItemset.html "class in org.apache.spark.mllib.fpm")<Item>> freqItemsets,  
                                                       scala.collection.Map<Item,Object> itemSupport,  
                                                       scala.reflect.ClassTag<Item> evidence$2)  
    Computes the association rules with confidence above `minConfidence`.  
    Parameters:  
    `freqItemsets` \- frequent itemset model obtained from [FPGrowth](../../../../../org/apache/spark/mllib/fpm/FPGrowth.html "class in org.apache.spark.mllib.fpm")  
    `itemSupport` \- map containing an item and its support  
    `evidence$2` \- (undocumented)  
    Returns:  
    a `RDD[Rule[Item}` containing the association rules. The rules will be able to compute also the lift metric.  
    * #### run  
    public <Item> [JavaRDD](../../../../../org/apache/spark/api/java/JavaRDD.html "class in org.apache.spark.api.java")<[AssociationRules.Rule](../../../../../org/apache/spark/mllib/fpm/AssociationRules.Rule.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")<[FPGrowth.FreqItemset](../../../../../org/apache/spark/mllib/fpm/FPGrowth.FreqItemset.html "class in org.apache.spark.mllib.fpm")<Item>> freqItemsets)  
    Java-friendly version of `run`.  
    Parameters:  
    `freqItemsets` \- (undocumented)  
    Returns:  
    (undocumented)