Example usage for weka.associations ItemSet setItem

Introduction

In this page you can find the example usage for weka.associations ItemSet setItem.

Prototype

public void setItem(int[] items) 

Source Link

Document

Sets an item sets

Usage

From source file:LabeledItemSet.java

License:Open Source License

/**
 * Generates rules out of item sets/*from   ww w  . ja v  a 2s  . co  m*/
 * @param minConfidence the minimum confidence
 * @param noPrune flag indicating whether the rules are pruned accoridng to the minimum confidence value
 * @return a set of rules
 */
public final FastVector[] generateRules(double minConfidence, boolean noPrune) {

    FastVector premises = new FastVector(), consequences = new FastVector(), conf = new FastVector();
    FastVector[] rules = new FastVector[3];
    ItemSet premise, consequence;

    // Generate all rules with class in the consequence. 
    premise = new ItemSet(m_totalTransactions);
    consequence = new ItemSet(m_totalTransactions);
    int[] premiseItems = new int[m_items.length];
    int[] consequenceItems = new int[1];
    System.arraycopy(m_items, 0, premiseItems, 0, m_items.length);
    consequence.setItem(consequenceItems);
    premise.setItem(premiseItems);
    consequence.setItemAt(m_classLabel, 0);
    consequence.setCounter(this.m_ruleSupCounter);
    premise.setCounter(this.m_counter);
    premises.addElement(premise);
    consequences.addElement(consequence);
    conf.addElement(new Double((double) this.m_ruleSupCounter / (double) this.m_counter));

    rules[0] = premises;
    rules[1] = consequences;
    rules[2] = conf;
    if (!noPrune)
        pruneRules(rules, minConfidence);

    return rules;
}

---