PatternRecognition07MLkNN.java

/*
 *    This program 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 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program 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 this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 *    PatternRecognition07MLkNN.java
 *    Copyright (C) 2009-2010 Aristotle University of Thessaloniki, Thessaloniki, Greece
 */
package mulan.experiments;

/**
 * Class replicating an experiment from a published paper
 *
 * @author Eleftherios Spyromitros-Xioufis (espyromi@csd.auth.gr)
 * @version 2010.12.10
 */
import java.util.ArrayList;
import java.util.List;

import mulan.classifier.lazy.MLkNN;
import mulan.data.MultiLabelInstances;
import mulan.evaluation.Evaluator;
import mulan.evaluation.MultipleEvaluation;
import mulan.evaluation.measure.AveragePrecision;
import mulan.evaluation.measure.Coverage;
import mulan.evaluation.measure.HammingLoss;
import mulan.evaluation.measure.Measure;
import mulan.evaluation.measure.OneError;
import mulan.evaluation.measure.RankingLoss;
import weka.core.TechnicalInformation;
import weka.core.Utils;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;

/**
 * Class replicating an experiment from a published paper
 *
 * @author Eleftherios Spyromitros-Xioufis (espyromi@csd.auth.gr)
 * @version 2010.12.10
 */
public class PatternRecognition07MLkNN extends Experiment {

    /**
     * Main class
     *
     * @param args command line arguments
     */
    public static void main(String[] args) {

        try {
            String path = Utils.getOption("path", args);
            String filestem = Utils.getOption("filestem", args);

            System.out.println("Loading the data set");
            MultiLabelInstances dataSet = new MultiLabelInstances(path + filestem + ".arff", path + filestem + ".xml");

            Evaluator eval = new Evaluator();
            MultipleEvaluation results;
            List<Measure> measures = new ArrayList<Measure>(5);
            measures.add(new HammingLoss());
            measures.add(new OneError());
            measures.add(new Coverage());
            measures.add(new RankingLoss());
            measures.add(new AveragePrecision());

            int numOfNeighbors;
            for (int i = 8; i <= 12; i++) {
                System.out.println("MLkNN Experiment for " + i + " neighbors:");
                numOfNeighbors = i;
                double smooth = 1.0;
                MLkNN mlknn = new MLkNN(numOfNeighbors, smooth);
                // mlknn.setDebug(true);
                results = eval.crossValidate(mlknn, dataSet, measures, 10);
                System.out.println(results);
            }

        } catch (Exception e) {
            e.printStackTrace();
        }

    }

    /**
     * Returns an instance of a TechnicalInformation object, containing detailed
     * information about the technical background of this class, e.g., paper
     * reference or book this class is based on.
     *
     * @return the technical information about this class
     */
    @Override
    public TechnicalInformation getTechnicalInformation() {
        TechnicalInformation result;

        result = new TechnicalInformation(Type.ARTICLE);
        result.setValue(Field.AUTHOR, "Min-Ling Zhang and Zhi-Hua Zhou");
        result.setValue(Field.TITLE, "ML-KNN: A lazy learning approach to multi-label learning");
        result.setValue(Field.JOURNAL, "Pattern Recogn.");
        result.setValue(Field.VOLUME, "40");
        result.setValue(Field.NUMBER, "7");
        result.setValue(Field.YEAR, "2007");
        result.setValue(Field.ISSN, "0031-3203");
        result.setValue(Field.PAGES, "2038--2048");
        result.setValue(Field.PUBLISHER, "Elsevier Science Inc.");
        result.setValue(Field.ADDRESS, "New York, NY, USA");

        return result;
    }
}