classif.PrototyperEUC.java Source code

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Here is the source code for classif.PrototyperEUC.java

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/*******************************************************************************
 * Copyright (C) 2014 Anonymized
 * Contributors:
 *    Anonymized
 * 
 * This file is part of ICDM2014SUBMISSION. 
 * This is a program related to the paper "Dynamic Time Warping Averaging of 
 * Time Series allows more Accurate and Faster Classification" submitted to the
 * 2014 Int. Conf. on Data Mining.
 * 
 * ICDM2014SUBMISSION 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, version 3 of the License.
 * 
 * ICDM2014SUBMISSION 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 ICDM2014SUBMISSION.  If not, see <http://www.gnu.org/licenses/>.
 ******************************************************************************/
package classif;

import java.util.ArrayList;
import java.util.HashMap;
import java.util.Random;

import org.apache.commons.math3.random.RandomDataGenerator;

import items.MonoDoubleItemSet;
import items.Sequence;
import items.ClassedSequence;
import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.core.Attribute;
import weka.core.Instance;
import weka.core.Instances;

public abstract class PrototyperEUC extends Prototyper {
    private static final long serialVersionUID = 922540906465712982L;

    protected abstract void buildSpecificClassifier(Instances data);

    @Override
    public double classifyInstance(Instance sample) throws Exception {
        // transform instance to sequence
        MonoDoubleItemSet[] sequence = new MonoDoubleItemSet[sample.numAttributes() - 1];
        int shift = (sample.classIndex() == 0) ? 1 : 0;
        for (int t = 0; t < sequence.length; t++) {
            sequence[t] = new MonoDoubleItemSet(sample.value(t + shift));
        }
        Sequence seq = new Sequence(sequence);

        double minD = Double.MAX_VALUE;
        String classValue = null;
        for (ClassedSequence s : prototypes) {
            double tmpD = seq.distanceEuc(s.sequence);
            if (tmpD < minD) {
                minD = tmpD;
                classValue = s.classValue;
            }
        }
        // System.out.println(prototypes.size());
        //      System.out.println(classValue);
        return sample.classAttribute().indexOfValue(classValue);
    }

    @Override
    public double evalErrorRate(ClassedSequence[] testSequences) {

        int nbCorrectlyClassified = 0;
        for (int s = 0; s < testSequences.length; s++) {
            Sequence seq = testSequences[s].sequence;
            double minD = Double.MAX_VALUE;
            String classValue = null;

            for (ClassedSequence proto : prototypes) {
                double tmpD = seq.distanceEuc(proto.sequence);
                if (tmpD < minD) {
                    minD = tmpD;
                    classValue = proto.classValue;
                }
            }

            if (classValue.equals(testSequences[s].classValue)) {
                nbCorrectlyClassified++;
            }

        }

        return 1.0 - 1.0 * nbCorrectlyClassified / (testSequences.length);
    }

}