meka.classifiers.multitarget.BCC.java Source code

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Here is the source code for meka.classifiers.multitarget.BCC.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.multitarget;

/**
 * BCC.java - The Bayesian Classifier Chains (BCC) method.
 * Multi-target version of BCC method (directly applicable) -- only the confidence information is different.
 * @see    meka.classifiers.multilabel.BCC
 * @author    Jesse Read 
 * @version   June 2012
 */
import java.util.Arrays;

import meka.classifiers.multilabel.ProblemTransformationMethod;
import weka.core.Instance;
import weka.classifiers.trees.J48;
import weka.core.RevisionUtils;

public class BCC extends meka.classifiers.multilabel.BCC implements MultiTargetClassifier {

    /** for serialization. */
    private static final long serialVersionUID = 2395428645144026318L;

    /**
     * Description to display in the GUI.
     * 
     * @return      the description
     */
    @Override
    public String globalInfo() {
        return "The Bayesian Classifier Chains (BCC) method.\n"
                + "Multi-target version of the BCC method (directly applicable).";
    }

    public BCC() {
        // default classifier for GUI
        this.m_Classifier = new J48();
    }

    @Override
    protected String defaultClassifierString() {
        // default classifier for CLI
        return "weka.classifiers.trees.J48";
    }

    @Override
    public double[] distributionForInstance(Instance x) throws Exception {
        int L = x.classIndex();
        double y_long[] = Arrays.copyOf(super.distributionForInstance(x), L * 2);
        Arrays.fill(y_long, L, y_long.length, 1.0);
        return y_long;
    }

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

    public static void main(String args[]) {
        ProblemTransformationMethod.evaluation(new meka.classifiers.multitarget.BCC(), args);
    }
}