Class AprioriItemSet

  • All Implemented Interfaces:
    java.io.Serializable, RevisionHandler

    public class AprioriItemSet
    extends ItemSet
    implements java.io.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: 9096 $
    Author:
    Eibe Frank (eibe@cs.waikato.ac.nz), Stefan Mutter (mutter@cs.waikato.ac.nz)
    See Also:
    Serialized Form
    • Constructor Detail

      • AprioriItemSet

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

      • 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 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
      • generateRulesBruteForce

        public final FastVector[] generateRulesBruteForce​(double minMetric,
                                                          int metricType,
                                                          FastVector hashtables,
                                                          int numItemsInSet,
                                                          int numTransactions,
                                                          double significanceLevel)
                                                   throws java.lang.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:
        java.lang.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 java.lang.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 FastVector singletons​(Instances instances)
                                     throws java.lang.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:
        java.lang.Exception - if singletons can't be generated successfully
      • mergeAllItemSets

        public static FastVector mergeAllItemSets​(FastVector 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