meka.classifiers.multilabel.PSt.java Source code

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Here is the source code for meka.classifiers.multilabel.PSt.java

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/*
 *   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 3 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, see <http://www.gnu.org/licenses/>.
 */

package meka.classifiers.multilabel;

import weka.core.Instance;
import meka.core.PSUtils;
import weka.core.RevisionUtils;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;
import weka.core.TechnicalInformationHandler;

/**
 * PSt.java -  Pruned Sets with a a threshold so as to be able to predict sets not seen in the training set.
 * <br>
 * See: Jesse Read. <i>A Pruned Problem Transformation Method for Multi-label Classification</i>. In Proc. of the NZ Computer Science Research Student Conference. Christchurch, New Zealand (2008).
 * @see PS
 * @author    Jesse Read (jmr30@cs.waikato.ac.nz)
 */
public class PSt extends PS implements TechnicalInformationHandler {

    /** for serialization. */
    private static final long serialVersionUID = -792705184263116856L;

    /**
     * Description to display in the GUI.
     * 
     * @return      the description
     */
    @Override
    public String globalInfo() {
        return "Pruned Sets with a a threshold so as to be able to predict sets not seen in the training set."
                + "For more information see:\n" + getTechnicalInformation().toString();
    }

    @Override
    public TechnicalInformation getTechnicalInformation() {
        TechnicalInformation result;

        result = new TechnicalInformation(Type.INPROCEEDINGS);
        result.setValue(Field.AUTHOR, "Jesse Read");
        result.setValue(Field.TITLE, "A Pruned Problem Transformation Method for Multi-label Classification");
        result.setValue(Field.BOOKTITLE,
                "NZ Computer Science Research Student Conference. Christchurch, New Zealand");
        result.setValue(Field.YEAR, "2008");

        return result;
    }

    @Override
    public double[] distributionForInstance(Instance x) throws Exception {

        int L = x.classIndex();

        // if there is only one class (as for e.g. in some hier. mtds) predict it
        if (L == 1)
            return new double[] { 1.0 };

        Instance x_ = PSUtils.convertInstance(x, L, m_InstancesTemplate); //convertInstance(x,L);
        //x_.setDataset(m_InstancesTemplate);

        // Get a classification
        return PSUtils.recombination_t(m_Classifier.distributionForInstance(x_), L, m_InstancesTemplate);
    }

    @Override
    public String getRevision() {
        return RevisionUtils.extract("$Revision: 9117 $");
    }

    public static void main(String args[]) {
        ProblemTransformationMethod.evaluation(new PSt(), args);
    }

}