/*
* 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 2 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, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
* MultiClassTransformationBase.java
* Copyright (C) 2009-2010 Aristotle University of Thessaloniki, Thessaloniki, Greece
*/
package mulan.transformations.multiclass;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import mulan.data.MultiLabelInstances;
import mulan.transformations.*;
import weka.core.Attribute;
import weka.core.Instance;
import weka.core.Instances;
/**
* The base class for multi-class transformation methods. It provides initial
* implementation of the {@link MultiClassTransformation} interface. All
* implementations of transformation methods should reuse this base class.
*
* @author Stavros
*/
public abstract class MultiClassTransformationBase implements Serializable, MultiClassTransformation {
/** the number of labels */
protected int numOfLabels;
/** the array with the label indices */
protected int[] labelIndices;
public Instances transformInstances(MultiLabelInstances mlData) throws Exception {
labelIndices = mlData.getLabelIndices();
numOfLabels = mlData.getNumLabels();
Instances data = mlData.getDataSet();
Instances transformed = new Instances(mlData.getDataSet(), 0);
// delete all labels
transformed = RemoveAllLabels.transformInstances(transformed, labelIndices);
// add single label attribute
ArrayList<String> classValues = new ArrayList<String>(numOfLabels);
for (int x = 0; x < numOfLabels; x++) {
classValues.add("Class" + (x + 1));
}
Attribute newClass = new Attribute("Class", classValues);
transformed.insertAttributeAt(newClass, transformed.numAttributes());
transformed.setClassIndex(transformed.numAttributes() - 1);
for (int instanceIndex = 0; instanceIndex < data.numInstances(); instanceIndex++) {
//System.out.println(data.instance(instanceIndex).toString());
List<Instance> result = transformInstance(data.instance(instanceIndex));
for (Instance instance : result) {
//System.out.println(instance.toString());
transformed.add(instance);
//System.out.println(transformed.instance(transformed.numInstances()-1));
}
}
return transformed;
}
abstract List<Instance> transformInstance(Instance instance);
}