cba.RuleItem.java Source code

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/*
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 * RuleItem.java
 * Copyright (C) 2004 University of Waikato, Hamilton, New Zealand
 *
 */

package cba;

import weka.associations.RuleGeneration;
import weka.core.Instances;
import weka.core.RevisionHandler;
import weka.core.RevisionUtils;

import java.io.Serializable;
import java.util.Hashtable;

/**
 * Class for storing an (class) association rule.
 * The premise and the consequence are stored each as separate item sets.
 * For every rule their expected predictive accuracy and the time of generation is stored.
 * These two measures allow to introduce a sort order for rules.
 *
 * @author Stefan Mutter
 * @version $Revision: 1.5 $
 */
public class RuleItem implements Comparable, Serializable, RevisionHandler {

    /** for serialization */
    private static final long serialVersionUID = -3761299128347476534L;

    /** The premise of a rule. */
    protected ItemSet m_premise;

    /** The consequence of a rule. */
    protected ItemSet m_consequence;

    /** The expected predictive accuracy of a rule. */
    protected double m_accuracy;

    /** The generation time of a rule. */
    protected int m_genTime;

    /**
     * Constructor for an empty RuleItem
     */
    public RuleItem() {

    }

    /**
     * Constructor that generates a RuleItem out of a given one
     * @param toCopy RuleItem to copy
     */
    public RuleItem(RuleItem toCopy) {

        m_premise = toCopy.m_premise;
        m_consequence = toCopy.m_consequence;
        m_accuracy = toCopy.m_accuracy;
        m_genTime = toCopy.m_genTime;
    }

    /**
     * Constructor
     * @param premise the premise of the future RuleItem
     * @param consequence the consequence of the future RuleItem
     * @param genTime the time of generation of the future RuleItem
     * @param ruleSupport support of the rule
     * @param m_midPoints the mid poitns of the intervals
     * @param m_priors Hashtable containing the estimated prior probablilities
     */
    public RuleItem(ItemSet premise, ItemSet consequence, int genTime, int ruleSupport, double[] m_midPoints,
            Hashtable m_priors) {

        m_premise = premise;
        m_consequence = consequence;
        m_accuracy = RuleGeneration.expectation((double) ruleSupport, m_premise.m_counter, m_midPoints, m_priors);
        //overflow, underflow
        if (Double.isNaN(m_accuracy) || m_accuracy < 0) {
            m_accuracy = Double.MIN_VALUE;
        }
        m_consequence.m_counter = ruleSupport;
        m_genTime = genTime;
    }

    /**
     * Constructs a new RuleItem if the support of the given rule is above the support threshold.
     * @param premise the premise
     * @param consequence the consequence
     * @param instances the instances
     * @param genTime the time of generation of the current premise and consequence
     * @param minRuleCount the support threshold
     * @param m_midPoints the mid points of the intervals
     * @param m_priors the estimated priori probabilities (in a hashtable)
     * @return a RuleItem if its support is above the threshold, null otherwise
     */
    public RuleItem generateRuleItem(ItemSet premise, ItemSet consequence, Instances instances, int genTime,
            int minRuleCount, double[] m_midPoints, Hashtable m_priors) {
        ItemSet rule = new ItemSet(instances.numInstances());
        rule.m_items = new int[(consequence.m_items).length];
        System.arraycopy(premise.m_items, 0, rule.m_items, 0, (premise.m_items).length);
        for (int k = 0; k < consequence.m_items.length; k++) {
            if (consequence.m_items[k] != -1)
                rule.m_items[k] = consequence.m_items[k];
        }
        for (int i = 0; i < instances.numInstances(); i++)
            rule.upDateCounter(instances.instance(i));
        int ruleSupport = rule.support();
        if (ruleSupport > minRuleCount) {
            RuleItem newRule = new RuleItem(premise, consequence, genTime, ruleSupport, m_midPoints, m_priors);
            return newRule;
        }
        return null;
    }

    //Note: this class has a natural ordering that is inconsistent with equals
    /**
     * compares two RuleItems and allows an ordering concerning
     * expected predictive accuracy and time of generation
     * Note: this class has a natural ordering that is inconsistent with equals
     * @param o RuleItem to compare
     * @return integer indicating the sort oder of the two RuleItems
     */
    public int compareTo(Object o) {

        if (this.m_accuracy == ((RuleItem) o).m_accuracy) {
            if ((this.m_genTime == ((RuleItem) o).m_genTime))
                return 0;
            if (this.m_genTime > ((RuleItem) o).m_genTime)
                return -1;
            if (this.m_genTime < ((RuleItem) o).m_genTime)
                return 1;
        }
        if (this.m_accuracy < ((RuleItem) o).m_accuracy)
            return -1;
        return 1;
    }

    /**
     * returns whether two RuleItems are equal
     * @param o RuleItem to compare
     * @return true if the rules are equal, false otherwise
     */
    public boolean equals(Object o) {

        if (o == null)
            return false;
        if (m_premise.equals(((RuleItem) o).m_premise) && m_consequence.equals(((RuleItem) o).m_consequence))
            return true;
        return false;
    }

    /**
     * Gets the expected predictive accuracy of a rule
     * @return the expected predictive accuracy of a rule stored as a RuleItem
     */
    public double accuracy() {

        return m_accuracy;
    }

    /**
     * Gets the premise of a rule
     * @return the premise of a rule stored as a RuleItem
     */
    public ItemSet premise() {

        return m_premise;
    }

    /**
     * Gets the consequence of a rule
     * @return the consequence of a rule stored as a RuleItem
     */
    public ItemSet consequence() {

        return m_consequence;
    }

    /**
     * Returns the revision string.
     * 
     * @return      the revision
     */
    public String getRevision() {
        return RevisionUtils.extract("$Revision: 1.5 $");
    }
}