sg.edu.nus.comp.nlp.ims.classifiers.CWekaModelTrainer.java Source code

Introduction

Here is the source code for sg.edu.nus.comp.nlp.ims.classifiers.CWekaModelTrainer.java

Source

/*******************************************************************************
 * IMS (It Makes Sense) -- NUS WSD System
 * Copyright (c) 2013 National University of Singapore.
 *
 * 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 sg.edu.nus.comp.nlp.ims.classifiers;

import sg.edu.nus.comp.nlp.ims.io.*;
import sg.edu.nus.comp.nlp.ims.lexelt.CModelInfo;
import sg.edu.nus.comp.nlp.ims.lexelt.ILexelt;
import sg.edu.nus.comp.nlp.ims.lexelt.IStatistic;
import weka.classifiers.Classifier;
import weka.core.Instances;

/**
 * call weka-3.2.3 classifier to train model for instances of a lexelt.
 *
 * @author zhongzhi
 *
 */
public class CWekaModelTrainer implements IModelTrainer {

    protected String m_ClassifierName = CMultiClassesSVM.class.getName();

    protected String[] m_Argvs = new String[] { "-I", "0" };

    protected int m_ClassIndex = -1;

    /**
     * default constructor
     */
    public CWekaModelTrainer() {
    }

    /**
     * constructor with specified classifier and its parameters
     *
     * @param p_ClassifierName
     *            classifier name
     * @param p_Argvs
     *            arguments
     * @param p_ClassIndex
     *            class index
     */
    public CWekaModelTrainer(String p_ClassifierName, String[] p_Argvs, int p_ClassIndex) {
        this.m_ClassifierName = p_ClassifierName;
        this.m_Argvs = p_Argvs;
        this.m_ClassIndex = p_ClassIndex;
    }

    /*
     * (non-Javadoc)
     * @see sg.edu.nus.comp.nlp.ims.classifier.IModelTrainer#train(java.lang.Object)
     */
    @Override
    public Object train(Object p_Lexelt) throws Exception {
        ILexelt lexelt = (ILexelt) p_Lexelt;
        CModelInfo retVal = new CModelInfo();
        retVal.lexelt = lexelt.getID();
        retVal.statistic = lexelt.getStatistic();
        if (((IStatistic) retVal.statistic).getTags().size() <= 1) {
            retVal.model = null;
        } else {
            String classifierName = this.m_ClassifierName;
            String[] args = this.m_Argvs.clone();
            ILexeltWriter lexeltWriter = new CWekaSparseLexeltWriter();
            Instances instances = (Instances) lexeltWriter.getInstances(lexelt);
            Classifier model = null;
            int classIdx = this.m_ClassIndex;
            if (classIdx < 0) {
                classIdx = instances.numAttributes() - 1;
            }
            instances.setClassIndex(classIdx);
            model = Classifier.forName(classifierName, args);
            model.buildClassifier(instances);
            retVal.model = model;
        }
        return retVal;
    }

    /*
     * (non-Javadoc)
     * @see sg.edu.nus.comp.nlp.ims.classifier.IModelTrainer#setOptions(java.lang.String[])
     */
    @Override
    public void setOptions(String[] p_Options) {
        if (p_Options.length < 2) {
            throw new IllegalArgumentException("modelDir statisticDir classIndex unknown");
        }
        this.m_ClassIndex = Integer.parseInt(p_Options[0]);
        this.m_ClassifierName = p_Options[1];
        this.m_Argvs = new String[p_Options.length - 2];
        System.arraycopy(p_Options, 2, this.m_Argvs, 0, p_Options.length - 2);
    }

}