/* * 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); }