de.lmu.ifi.dbs.elki.algorithm
Class APRIORI

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<BitVector,AprioriResult>
          de.lmu.ifi.dbs.elki.algorithm.APRIORI

All Implemented Interfaces:

Algorithm<BitVector,AprioriResult>, Parameterizable

@Title(value="APRIORI: Algorithm for Mining Association Rules")
@Description(value="Searches for frequent itemsets")
@Reference(authors="R. Agrawal, R. Srikant",
           title="Fast Algorithms for Mining Association Rules in Large Databases",
           booktitle="Proc. 20th Int. Conf. on Very Large Data Bases (VLDB \'94), Santiago de Chile, Chile 1994",
           url="http://www.acm.org/sigmod/vldb/conf/1994/P487.PDF")
public class APRIORI
extends AbstractAlgorithm<BitVector,AprioriResult>

Provides the APRIORI algorithm for Mining Association Rules.

Reference:
R. Agrawal, R. Srikant: Fast Algorithms for Mining Association Rules in Large Databases.
In Proc. 20th Int. Conf. on Very Large Data Bases (VLDB '94), Santiago de Chile, Chile 1994.

Author:

Arthur Zimek

Field Summary

private double	minfreq Holds the value of MINFREQ_PARAM.
static OptionID	MINFREQ_ID OptionID for MINFREQ_PARAM
private DoubleParameter	MINFREQ_PARAM Optional parameter to specify the threshold for minimum frequency, must be a double greater than or equal to 0 and less than or equal to 1.
private int	minsupp Holds the value of MINSUPP_PARAM.
static OptionID	MINSUPP_ID OptionID for MINSUPP_PARAM
private IntParameter	MINSUPP_PARAM Parameter to specify the threshold for minimum support as minimally required number of transactions, must be an integer equal to or greater than 0.

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug, logger

Constructor Summary

APRIORI(Parameterization config)
Constructor, adhering to Parameterizable

Method Summary

protected BitSet[]	frequentItemsets(Map<BitSet,Integer> support, BitSet[] candidates, Database<BitVector> database) Returns the frequent BitSets out of the given BitSets with respect to the given database.
protected BitSet[]	join(BitSet[] frequentItemsets) Returns a set of BitSets generated by joining pairs of given BitSets (relying on the given BitSets being sorted), increasing the length by 1.
protected BitSet[]	prune(Map<BitSet,Integer> support, BitSet[] candidates, int size) Prunes a given set of candidates to keep only those BitSets where all subsets of bits flipping one bit are frequent already.
protected AprioriResult	runInTime(Database<BitVector> database) Performs the APRIORI algorithm on the given database.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

isTime, isVerbose, run, setTime, setVerbose

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, progress, verbose, warning

Methods inherited from class java.lang.Object

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

Field Detail

MINFREQ_ID

public static final OptionID MINFREQ_ID

OptionID for MINFREQ_PARAM

MINFREQ_PARAM

private final DoubleParameter MINFREQ_PARAM

Optional parameter to specify the threshold for minimum frequency, must be a double greater than or equal to 0 and less than or equal to 1. Alternatively to parameter MINSUPP_PARAM).

Key: -apriori.minfreq

minfreq

private double minfreq

Holds the value of MINFREQ_PARAM.

MINSUPP_ID

public static final OptionID MINSUPP_ID

OptionID for MINSUPP_PARAM

MINSUPP_PARAM

private final IntParameter MINSUPP_PARAM

Parameter to specify the threshold for minimum support as minimally required number of transactions, must be an integer equal to or greater than 0. Alternatively to parameter MINFREQ_PARAM - setting MINSUPP_PARAM is slightly preferable over setting MINFREQ_PARAM in terms of efficiency.

Key: -apriori.minsupp

minsupp

private int minsupp

Holds the value of MINSUPP_PARAM.

Constructor Detail

APRIORI

public APRIORI(Parameterization config)

Constructor, adhering to Parameterizable

Parameters:

config - Parameterization

Method Detail

runInTime

protected AprioriResult runInTime(Database<BitVector> database)
                           throws IllegalStateException

Performs the APRIORI algorithm on the given database.

Specified by:

runInTime in class AbstractAlgorithm<BitVector,AprioriResult>

Parameters:

database - the Database to run APRIORI on

Returns:

the AprioriResult learned by this APRIORI

Throws:

IllegalStateException - if the algorithm has not been initialized properly (e.g. the setParameters(String[]) method has been failed to be called).

prune

protected BitSet[] prune(Map<BitSet,Integer> support,
                         BitSet[] candidates,
                         int size)

Prunes a given set of candidates to keep only those BitSets where all subsets of bits flipping one bit are frequent already.

Parameters:

support - Support map

candidates - the candidates to be pruned

size - size of the database

Returns:

a set of BitSets where all subsets of bits flipping one bit are frequent already

join

protected BitSet[] join(BitSet[] frequentItemsets)

Returns a set of BitSets generated by joining pairs of given BitSets (relying on the given BitSets being sorted), increasing the length by 1.

Parameters:

frequentItemsets - the BitSets to be joined

Returns:

a set of BitSets generated by joining pairs of given BitSets, increasing the length by 1

frequentItemsets

protected BitSet[] frequentItemsets(Map<BitSet,Integer> support,
                                    BitSet[] candidates,
                                    Database<BitVector> database)

Returns the frequent BitSets out of the given BitSets with respect to the given database.

Parameters:

support - Support map.

candidates - the candidates to be evaluated

database - the database to evaluate the candidates on

Returns:

the frequent BitSets out of the given BitSets with respect to the given database