eu.monnetproject.translation.jmert.SVMRankOptimizer Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of translation.jmert Show documentation
com.github.monnetproject.translation.jmert OSGi Bundle from the Monnet Project's translation.project project.
The newest version!
/**
 * *******************************************************************************
 * Copyright (c) 2011, Monnet Project All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met: *
 * Redistributions of source code must retain the above copyright notice, this
 * list of conditions and the following disclaimer. * Redistributions in binary
 * form must reproduce the above copyright notice, this list of conditions and
 * the following disclaimer in the documentation and/or other materials provided
 * with the distribution. * Neither the name of the Monnet Project nor the names
 * of its contributors may be used to endorse or promote products derived from
 * this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED. IN NO EVENT SHALL THE MONNET PROJECT BE LIABLE FOR ANY
 * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 * *******************************************************************************
 */
package eu.monnetproject.translation.jmert;

import eu.monnetproject.translation.Feature;
import eu.monnetproject.translation.monitor.Messages;
import java.util.ArrayList;
import java.util.Collection;
import java.util.List;
import java.util.Set;

/**
 *
 * @author John McCrae
 */
public class SVMRankOptimizer implements Optimizer {

    private static final double C = Double.parseDouble(System.getProperty("C", "1"));

    @Override
    public double[] optimizeFeatures(List> nBests, Feature[] initWeights, int nIters, Set unused) {
        Messages.info("Optimizing " + nBests.size() + " interesting nBest lists");
        
        int n = 0;
        final ArrayList x = new ArrayList();
        final ArrayList spA = new ArrayList();
        int row_no = 0;
        for (Collection translations : nBests) {
            for (JMertTranslation translation : translations) {
                double[] x2 = new double[initWeights.length];
                for (Feature f : translation.features) {
                    x2[indexOfName(initWeights, f.name)] = f.score;
                }
                x.add(x2);
                int row_no2 = n;
                for (JMertTranslation translation2 : translations) {
                    if (row_no2 == row_no) {
                        row_no2++;
                        continue;
                    }
                    if (translation.score > translation2.score) {
                        spA.add(new int[]{row_no, row_no2});
                    }
                    row_no2++;
                }
                row_no++;
            }
            n += translations.size();
        }

        final SVMRank rank = new SVMRank(x.toArray(new double[x.size()][]), spA.toArray(new int[spA.size()][]), C);
        
        final double[] wts = rank.solve();
        
        if (allZero(wts)) {
            return toDoubleArray(initWeights);
        }
        double sumWts = 0.0;
        for (int i = 0; i < wts.length; i++) {
            if(wts[i] < 0) {
                wts[i] = 1e-20;
            }
            sumWts += wts[i];
        }
        
        if(sumWts == 0.0) {
            sumWts = 1e-20;
        }
        
        for (int i = 0; i < wts.length; i++) {
            wts[i] /= sumWts;
        }
        return wts;
    }

    private int indexOfName(Feature[] feature, String name) {
        for (int i = 0; i < feature.length; i++) {
            if (feature[i].name.equals(name)) {
                return i;
            }
        }
        throw new RuntimeException("Unknown feature " + name);
    }

    private boolean allZero(double[] wts) {
        for (int i = 0; i < wts.length; i++) {
            if (wts[i] != 0.0) {
                return false;
            }
        }
        return true;
    }

    private double[] toDoubleArray(Feature[] initWeights) {
        double[] da = new double[initWeights.length];
        for (int i = 0; i < initWeights.length; i++) {
            da[i] = initWeights[i].score;
        }
        return da;
    }
}