org.apache.spark.mllib.fpm

Class FPGrowth

Object

org.apache.spark.mllib.fpm.FPGrowth

All Implemented Interfaces:

java.io.Serializable, Logging

public class FPGrowth
extends Object
implements Logging, scala.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.

param: minSupport the minimal support level of the frequent pattern, any pattern that appears more than (minSupport * size-of-the-dataset) times will be output param: numPartitions number of partitions used by parallel FP-growth

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.

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

Modifier and Type	Method and Description
<Item,Basket extends Iterable<Item>> FPGrowthModel<Item>	run(JavaRDD<Basket> data) Java-friendly version of run.
<Item> FPGrowthModel<Item>	run(RDD<Object> data, scala.reflect.ClassTag<Item> 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

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

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 setMinSupport(double minSupport)

Sets the minimal support level (default: 0.3).

Parameters:

minSupport - (undocumented)

Returns:

(undocumented)

setNumPartitions

public FPGrowth 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<Item> run(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

run

public <Item,Basket extends Iterable<Item>> FPGrowthModel<Item> run(JavaRDD<Basket> data)

Java-friendly version of run.

Parameters:

data - (undocumented)

Returns:

(undocumented)