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Class weka.associations.ItemSet 

java.lang.Object
   |
   +----weka.associations.ItemSet
public class ItemSet
extends Object
implements Serializable
Class for storing a set of items. Item sets are stored in a lexicographic order, which is determined by the header information of the set of instances used for generating the set of items. All methods in this class assume that item sets are stored in lexicographic order.

Version:
$Revision: 1.3 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Index

o ItemSet()

Method Index

o confidenceForRule(ItemSet, ItemSet)
Outputs the confidence for a rule.
o containedBy(Instance)
Checks if an instance contains an item set.
o deleteItemSets(FastVector, int)
Deletes all item sets that don't have minimum support.
o equals(Object)
Tests if two item sets are equal.
o generateRules(double, FastVector, int)
Generates all rules for an item set.
o generateRulesBruteForce(double, FastVector, int, int, double)
Generates all significant rules for an item set.
o getHashtable(FastVector, int)
Return a hashtable filled with the given item sets.
o hashCode()
Produces a hash code for a item set.
o mergeAllItemSets(FastVector, int)
Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
o pruneItemSets(FastVector, Hashtable)
Prunes a set of (k)-item sets using the given (k-1)-item sets.
o pruneRules(FastVector[], double)
Prunes a set of rules.
o singletons(Instances)
Converts the header info of the given set of instances into a set of item sets (singletons).
o subtract(ItemSet)
Subtracts an item set from another one.
o support()
Outputs the support for an item set.
o toString(Instances)
Returns the contents of an item set as a string.
o upDateCounter(Instance)
Updates counter of item set with respect to given transaction.
o upDateCounters(FastVector, Instances)
Updates counters for a set of item sets and a set of instances.

Constructors

o ItemSet 
 public ItemSet()

Methods

o confidenceForRule 
 public static double confidenceForRule(ItemSet premise,
                                        ItemSet consequence)
Outputs the confidence for a rule.

Parameters:
premise - the premise of the rule
consequence - the consequence of the rule
Returns:
the confidence on the training data
o containedBy 
 public final boolean containedBy(Instance instance)
Checks if an instance contains an item set.

Parameters:
instance - the instance to be tested
Returns:
true if the given instance contains this item set
o deleteItemSets 
 public static FastVector deleteItemSets(FastVector itemSets,
                                         int minSupport)
Deletes all item sets that don't have minimum support.

Parameters:
itemSets - the set of item sets to be pruned
minSupport - the minimum number of transactions to be covered
Returns:
the reduced set of item sets
o equals 
 public final boolean equals(Object itemSet)
Tests if two item sets are equal.

Parameters:
itemSet - another item set
Returns:
true if this item set contains the same items as the given one
Overrides:
equals in class Object
o generateRules 
 public final FastVector[] generateRules(double minConfidence,
                                         FastVector hashtables,
                                         int numItemsInSet)
Generates all rules for an item set.

Parameters:
minConfidence - the minimum confidence the rules have to have
hashtables - containing all(!) previously generated item sets
numItemsInSet - the size of the item set for which the rules are to be generated
Returns:
all the rules with minimum confidence for the given item set
o generateRulesBruteForce 
 public final FastVector[] generateRulesBruteForce(double minConfidence,
                                                   FastVector hashtables,
                                                   int numItemsInSet,
                                                   int numTransactions,
                                                   double significanceLevel)
Generates all significant rules for an item set.

Parameters:
minConfidence - the minimum confidence the rules have to have
hashtables - containing all(!) previously generated item sets
numItemsInSet - the size of the item set for which the rules are to be generated
the - significance level for testing the rules
Returns:
all the rules with minimum confidence for the given item set
o getHashtable 
 public static Hashtable getHashtable(FastVector itemSets,
                                      int initialSize)
Return a hashtable filled with the given item sets.

Parameters:
itemSets - the set of item sets to be used for filling the hash table
initialSize - the initial size of the hashtable
Returns:
the generated hashtable
o hashCode 
 public final int hashCode()
Produces a hash code for a item set.

Returns:
a hash code for a set of items
Overrides:
hashCode in class Object
o mergeAllItemSets 
 public static FastVector mergeAllItemSets(FastVector itemSets,
                                           int size)
Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.

Parameters:
itemSets - the set of (k-1)-item sets
size - the value of (k-1)
Returns:
the generated (k)-item sets
o pruneItemSets 
 public static FastVector pruneItemSets(FastVector toPrune,
                                        Hashtable kMinusOne)
Prunes a set of (k)-item sets using the given (k-1)-item sets.

Parameters:
toPrune - the set of (k)-item sets to be pruned
kMinusOne - the (k-1)-item sets to be used for pruning
Returns:
the pruned set of item sets
o pruneRules 
 public static void pruneRules(FastVector rules[],
                               double minConfidence)
Prunes a set of rules.

Parameters:
rules - a two-dimensional array of lists of item sets. The first list of item sets contains the premises, the second one the consequences.
minConfidence - the minimum confidence the rules have to have
o singletons 
 public static FastVector singletons(Instances instances) throws Exception
Converts the header info of the given set of instances into a set of item sets (singletons). The ordering of values in the header file determines the lexicographic order.

Parameters:
instances - the set of instances whose header info is to be used
Returns:
a set of item sets, each containing a single item
Throws: Exception
if singletons can't be generated successfully
o subtract 
 public final ItemSet subtract(ItemSet toSubtract)
Subtracts an item set from another one.

Parameters:
toSubtract - the item set to be subtracted from this one.
Returns:
an item set that only contains items form this item sets that are not contained by toSubtract
o support 
 public final int support()
Outputs the support for an item set.

Returns:
the support
o toString 
 public final String toString(Instances instances)
Returns the contents of an item set as a string.

Parameters:
instances - contains the relevant header information
Returns:
string describing the item set
o upDateCounter 
 public final void upDateCounter(Instance instance)
Updates counter of item set with respect to given transaction.

Parameters:
instance - the instance to be used for ubdating the counter
o upDateCounters 
 public static void upDateCounters(FastVector itemSets,
                                   Instances instances)
Updates counters for a set of item sets and a set of instances.

Parameters:
itemSets - the set of item sets which are to be updated
instances - the instances to be used for updating the counters 
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