Package weka.associations

Class AprioriItemSet

java.lang.Object
weka.associations.ItemSet
weka.associations.AprioriItemSet
All Implemented Interfaces:
Serializable, RevisionHandler
public class AprioriItemSet extends ItemSet implements Serializable, RevisionHandler
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. The class provides methods that are used in the Apriori algorithm to construct association rules.
Version:
$Revision: 12014 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz), Stefan Mutter (mutter@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • AprioriItemSet

      public AprioriItemSet(int totalTrans)
      Constructor
      Parameters:
      totalTrans - the total number of transactions in the data

  • Method Details

    • confidenceForRule

      public static double confidenceForRule(AprioriItemSet premise, AprioriItemSet 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

    • liftForRule

      public double liftForRule(AprioriItemSet premise, AprioriItemSet consequence, int consequenceCount)
      Outputs the lift for a rule. Lift is defined as:
      confidence / prob(consequence)
      Parameters:
      premise - the premise of the rule
      consequence - the consequence of the rule
      consequenceCount - how many times the consequence occurs independent of the premise
      Returns:
      the lift on the training data

    • leverageForRule

      public double leverageForRule(AprioriItemSet premise, AprioriItemSet consequence, int premiseCount, int consequenceCount)
      Outputs the leverage for a rule. Leverage is defined as:
      prob(premise & consequence) - (prob(premise) * prob(consequence))
      Parameters:
      premise - the premise of the rule
      consequence - the consequence of the rule
      premiseCount - how many times the premise occurs independent of the consequent
      consequenceCount - how many times the consequence occurs independent of the premise
      Returns:
      the leverage on the training data

    • convictionForRule

      public double convictionForRule(AprioriItemSet premise, AprioriItemSet consequence, int premiseCount, int consequenceCount)
      Outputs the conviction for a rule. Conviction is defined as:
      prob(premise) * prob(!consequence) / prob(premise & !consequence)
      Parameters:
      premise - the premise of the rule
      consequence - the consequence of the rule
      premiseCount - how many times the premise occurs independent of the consequent
      consequenceCount - how many times the consequence occurs independent of the premise
      Returns:
      the conviction on the training data

    • generateRules

      public ArrayList<Object>[] generateRules(double minConfidence, ArrayList<Hashtable<ItemSet,Integer>> 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

    • generateRulesBruteForce

      public final ArrayList<Object>[] generateRulesBruteForce(double minMetric, int metricType, ArrayList<Hashtable<ItemSet,Integer>> hashtables, int numItemsInSet, int numTransactions, double significanceLevel) throws Exception
      Generates all significant rules for an item set.
      Parameters:
      minMetric - the minimum metric (confidence, lift, leverage, improvement) the rules have to have
      metricType - (confidence=0, lift, leverage, improvement)
      hashtables - containing all(!) previously generated item sets
      numItemsInSet - the size of the item set for which the rules are to be generated
      numTransactions -
      significanceLevel - the significance level for testing the rules
      Returns:
      all the rules with minimum metric for the given item set
      Throws:
      Exception - if something goes wrong

    • subtract

      public final AprioriItemSet subtract(AprioriItemSet 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

    • toString

      public final String toString(Instances instances)
      Returns the contents of an item set as a string.
      Overrides:
      toString in class ItemSet
      Parameters:
      instances - contains the relevant header information
      Returns:
      string describing the item set

    • singletons

      public static ArrayList<Object> singletons(Instances instances, boolean treatZeroAsMissing) 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

    • mergeAllItemSets

      public static ArrayList<Object> mergeAllItemSets(ArrayList<Object> itemSets, int size, int totalTrans)
      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)
      totalTrans - the total number of transactions in the data
      Returns:
      the generated (k)-item sets

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Overrides:
      getRevision in class ItemSet
      Returns:
      the revision