meka.classifiers.multilabel.incremental.RTUpdateable.java Source code

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Here is the source code for meka.classifiers.multilabel.incremental.RTUpdateable.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.incremental;

import meka.classifiers.multilabel.IncrementalMultiLabelClassifier;
import meka.classifiers.multilabel.RT;
import weka.classifiers.UpdateableClassifier;
import weka.classifiers.trees.HoeffdingTree;
import weka.core.Instance;

/**
 * RTUpdateable.java - Updateable RT.
 * Must be given an UpdateableClassifier base classifier.
 * @see RT
 * @author    Jesse Read
 * @version October, 2011
 */
public class RTUpdateable extends RT implements IncrementalMultiLabelClassifier {

    /** for serialization. */
    private static final long serialVersionUID = 3766003607269541755L;

    @Override
    public String globalInfo() {
        return "Updateable RT\nMust be run with an Updateable base classifier.";
    }

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

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

    @Override
    public void updateClassifier(Instance x) throws Exception {

        int L = x.classIndex();

        for (int j = 0; j < L; j++) {
            if (x.value(j) > 0.0) {
                Instance x_j = convertInstance(x);
                x_j.setClassValue(j);
                ((UpdateableClassifier) m_Classifier).updateClassifier(x_j);
            }
        }
    }

    public static void main(String args[]) {
        IncrementalEvaluation.runExperiment(new RTUpdateable(), args);
    }

}