Package org.apache.spark.mllib.fpm

Class AssociationRules

Object

org.apache.spark.mllib.fpm.AssociationRules

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging

public class AssociationRules
extends Object
implements org.apache.spark.internal.Logging, 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	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.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Constructor Summary

Constructors

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

Method Summary

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

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.internal.Logging

initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

Constructor Details

AssociationRules

public AssociationRules()

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

Method Details

setMinConfidence

public AssociationRules setMinConfidence(double minConfidence)

Sets the minimal confidence (default: 0.8).

Parameters:

minConfidence - (undocumented)

Returns:

(undocumented)

run

public <Item> RDD<AssociationRules.Rule<Item>> run(RDD<FPGrowth.FreqItemset<Item>> freqItemsets,
 scala.reflect.ClassTag<Item> evidence$1)

Computes the association rules with confidence above minConfidence.

Parameters:

freqItemsets - frequent itemset model obtained from FPGrowth

evidence$1 - (undocumented)

Returns:

a RDD[Rule[Item} containing the association rules.

run

public <Item> RDD<AssociationRules.Rule<Item>> run(RDD<FPGrowth.FreqItemset<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

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<AssociationRules.Rule<Item>> run(JavaRDD<FPGrowth.FreqItemset<Item>> freqItemsets)

Java-friendly version of run.

Parameters:

freqItemsets - (undocumented)

Returns:

(undocumented)