package ca.pfv.spmf.test; import java.io.IOException; import java.io.UnsupportedEncodingException; import java.net.URL; import ca.pfv.spmf.algorithms.frequentpatterns.cori.AlgoCORI; import ca.pfv.spmf.algorithms.frequentpatterns.eclat.AlgoEclat; import ca.pfv.spmf.input.transaction_database_list_integers.TransactionDatabase; /** * Example of how to use the CORI algorithm from the source code. * @author Philippe Fournier-Viger - 2015 */ public class MainTestCORI_saveToFile { public static void main(String [] arg) throws IOException{ // the file paths String input = fileToPath("contextPasquier99.txt"); // the database String output = ".//output.txt"; // the path for saving the frequent itemsets found // minimum support double minsup = 0.8; // means 2 transaction (we used a relative support) // minimum bond double minbond = 0.2; // the minimum bond threhsold // Loading the transaction database TransactionDatabase database = new TransactionDatabase(); try { database.loadFile(input); } catch (IOException e) { e.printStackTrace(); } // context.printContext(); // Applying the ECLAT algorithm AlgoCORI algo = new AlgoCORI(); algo.runAlgorithm(output, database, minsup, minbond, false); // if you change use "true" in the line above, ECLAT will use // a triangular matrix for counting support of itemsets of size 2. // For some datasets it should make the algorithm faster. algo.printStats(); } public static String fileToPath(String filename) throws UnsupportedEncodingException{ URL url = MainTestCORI_saveToFile.class.getResource(filename); return java.net.URLDecoder.decode(url.getPath(),"UTF-8"); } }