package ca.pfv.spmf.algorithms.frequentpatterns.itemsettree;
/**
* This class represents an association rule.
*
* Copyright (c) 2008-2012 Philippe Fournier-Viger
*
* This file is part of the SPMF DATA MINING SOFTWARE
* (http://www.philippe-fournier-viger.com/spmf).
*
* SPMF 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 3 of the License, or
* (at your option) any later version.
*
* SPMF 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 SPMF. If not, see <http://www.gnu.org/licenses/>.
*/
public class AssociationRuleIT {
// support of the rule
public int support;
// confidence of the rule
public double confidence;
// the antecedent of the rule
public int[] itemset1;
// the consequent of the rule
public int[] itemset2;
/**
* Get a string representation of this rule
*/
public String toString(){
// create a StringBuilder
StringBuilder buffer = new StringBuilder();
// append items from the antecedent
buffer.append("[ ");
for(Integer item : itemset1){
buffer.append(item);
buffer.append(" ");
}
// arrow
buffer.append(" ] ==> [");
// append items from the consequent
for(Integer item : itemset2){
buffer.append(item);
buffer.append(" ");
}
// append the support and confidence
buffer.append(" ] #SUP: ");
buffer.append(support);
buffer.append(" #CONF:");
buffer.append(confidence);
buffer.append("\n");
// return the string
return buffer.toString();
}
}