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(); } }