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");
}
}