meka.classifiers.multitarget.RAkELd.java Source code

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

import meka.classifiers.multilabel.ProblemTransformationMethod;
import meka.core.*;
import meka.filters.multilabel.SuperNodeFilter;
import weka.classifiers.AbstractClassifier;
import weka.classifiers.Classifier;
import weka.core.*;

import java.util.*;

/**
 * TODO
 * @see      meka.classifiers.multilabel.RAkELd
 * @author    Jesse Read 
 * @version October 2015
 */
public class RAkELd extends NSR {

    /** for serialization. */
    private static final long serialVersionUID = -6208388889440497990L;

    protected Classifier m_Classifiers[] = null;
    protected Instances m_InstancesTemplates[] = null;
    int m_K = 3;
    int m_M = 10;
    protected int kMap[][] = null;
    protected int vMap[][][] = null; // TODO use this to speed things up

    /**
     * Description to display in the GUI.
     * 
     * @return      the description
     */
    @Override
    public String globalInfo() {
        return "Takes RAndom partition of labELs; like RAkEL but labelsets are disjoint / non-overlapping subsets.";
    }

    @Override
    public void buildClassifier(Instances D) throws Exception {
        /*
        This is a slow way of doing things at the moment, making use of multitarget.SCC functionality,
        even though multilabel.RAkELd is not a meta multi-label classifier.
         */

        int L = D.classIndex();
        int N = D.numInstances();
        Random r = new Random(m_S);

        // Note: a slightly round-about way of doing it:
        int num = (int) Math.ceil(L / m_K);
        kMap = SuperLabelUtils.generatePartition(A.make_sequence(L), num, r, true);
        m_M = kMap.length;
        vMap = new int[m_M][][];
        m_Classifiers = AbstractClassifier.makeCopies(m_Classifier, m_M);
        m_InstancesTemplates = new Instances[m_M];

        if (getDebug())
            System.out.println("Building " + m_M + " models of " + m_K + " partitions:");

        D = SuperLabelUtils.SLTransformation(D, kMap, m_P, m_N);

        for (int i = 0; i < m_M; i++) {

            /*
            if (getDebug()) 
               System.out.println("\tpartitioning model "+(i+1)+"/"+m_M+": "+Arrays.toString(kMap[i])+", P="+m_P+", N="+m_N);
                
            Instances D_i = SuperLabelUtils.makePartitionDataset(D,kMap[i],m_P,m_N);
            */

            Instances D_i = F.keepLabels(D, D.classIndex(), new int[] { i });
            D_i.setClassIndex(0);

            //vMap[i] = SuperLabelUtils.extractValues(D_i);

            if (getDebug())
                System.out.println("\tbuilding model " + (i + 1) + "/" + m_M + ": " + Arrays.toString(kMap[i]));

            m_Classifiers[i].buildClassifier(D_i);
            m_InstancesTemplates[i] = new Instances(D_i, 0);

        }

    }

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

        int L = x.classIndex();

        HashMap<Integer, Double> votes[] = new HashMap[L];
        for (int j = 0; j < L; j++) {
            votes[j] = new HashMap<Integer, Double>();
        }

        for (int m = 0; m < m_M; m++) {

            // Transform instance
            Instance x_m = PSUtils.convertInstance(x, L, m_InstancesTemplates[m]);
            x_m.setDataset(m_InstancesTemplates[m]);

            // Get a meta classification
            int yp_j = (int) m_Classifiers[m].classifyInstance(x_m); // e.g., 2

            int values[] = SuperLabelUtils.decodeValue(m_InstancesTemplates[m].classAttribute().value(yp_j));

            int k_indices[] = SuperLabelUtils.decodeClass(m_InstancesTemplates[m].classAttribute().name());

            // Vote with classification
            for (int j_k = 0; j_k < k_indices.length; j_k++) {
                //int i = k_indices[j_k];         // original indices
                int j = kMap[m][j_k]; // original indices
                Double score = votes[j].get(values[j_k]);
                votes[j].put(values[j_k], (score == null) ? 1. : score + 1.);
            }

        }

        double y[] = SuperLabelUtils.convertVotesToDistributionForInstance(votes);

        return y;
    }

    @Override
    public String toString() {
        if (kMap == null)
            return "No model built yet";
        StringBuilder s = new StringBuilder("{");
        for (int k = 0; k < m_M; k++) {
            s.append(Arrays.toString(kMap[k]));
        }
        return s.append("}").toString();
    }

    /**
     * GetK - Get the k parameter (size of partitions).
     */
    public int getK() {
        return m_K;
    }

    /**
     * SetP - Sets the k parameter (size of partitions)
     */
    public void setK(int k) {
        m_K = k;
    }

    public String kTipText() {
        return "The number of labels in each partition -- should be 1 <= k < (L/2) where L is the total number of labels.";
    }

    @Override
    public Enumeration listOptions() {
        Vector result = new Vector();
        result.addElement(new Option("\t" + kTipText(), "k", 1, "-k <num>"));
        OptionUtils.add(result, super.listOptions());
        return OptionUtils.toEnumeration(result);
    }

    @Override
    public void setOptions(String[] options) throws Exception {
        setK(OptionUtils.parse(options, 'k', 3));
        super.setOptions(options);
    }

    @Override
    public String[] getOptions() {
        List<String> result = new ArrayList<>();
        OptionUtils.add(result, 'k', getK());
        OptionUtils.add(result, super.getOptions());
        return OptionUtils.toArray(result);
    }

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

    public static void main(String args[]) {
        //ProblemTransformationMethod.evaluation(new RAkELd(), args);
        RAkELd h = new RAkELd();
        try {
            String args2[] = Utils.splitOptions(
                    "-t /home/jesse/Local/Data/m0-SFLARE.arff -verbosity 5 -R -W weka.classifiers.functions.SMO -k 2 -output-debug-info");
            //String args2[] = Utils.splitOptions("-t /home/jesse/Local/Data/X-EMOT.arff -verbosity 5 -R -W weka.classifiers.functions.SMO -k 2 -output-debug-info");
            ProblemTransformationMethod.evaluation(h, args2);
        } catch (Exception e) {
        }
    }

}