package ca.pfv.spmf.test; import java.io.FileNotFoundException; import java.io.IOException; import java.io.UnsupportedEncodingException; import java.net.URL; import ca.pfv.spmf.algorithms.associationrules.agrawal94_association_rules.AlgoAgrawalFaster94; import ca.pfv.spmf.algorithms.associationrules.agrawal94_association_rules.AssocRules; import ca.pfv.spmf.algorithms.frequentpatterns.cfpgrowth.AlgoCFPGrowth; import ca.pfv.spmf.patterns.itemset_array_integers_with_count.Itemsets; /** * Example of how to mine all association rules with CFPGROWTH with the lift, * from the source code. * * @author Philippe Fournier-Viger (Copyright 2008) */ public class MainTestAllAssociationRules_CFPGrowth_saveToMemory_with_lift { public static void main(String [] arg) throws FileNotFoundException, IOException{ String input = fileToPath("contextIGB.txt"); String MISfile = fileToPath("MIS.txt"); // STEP 1: Applying the CFP-GROWTH algorithm to find frequent itemsets AlgoCFPGrowth cfpgrowth = new AlgoCFPGrowth(); Itemsets patterns = cfpgrowth.runAlgorithm(input, null, MISfile); // patterns.printItemsets(database.size()); int databaseSize = cfpgrowth.getDatabaseSize(); cfpgrowth.printStats(); // STEP 2: Generating all rules from the set of frequent itemsets (based on Agrawal & Srikant, 94) double minlift = 0.1; double minconf = 0.50; AlgoAgrawalFaster94 algoAgrawal = new AlgoAgrawalFaster94(); // the next line run the algorithm. // Note: we pass null as output file path, because we don't want // to save the result to a file, but keep it into memory. AssocRules rules = algoAgrawal.runAlgorithm(patterns,null, databaseSize, minconf, minlift); algoAgrawal.printStats(); rules.printRulesWithLift(databaseSize); } public static String fileToPath(String filename) throws UnsupportedEncodingException{ URL url = MainTestAllAssociationRules_CFPGrowth_saveToMemory_with_lift.class.getResource(filename); return java.net.URLDecoder.decode(url.getPath(),"UTF-8"); } }