Java tutorial
/* * NoChange.java * Copyright (C) 2013 University of Waikato, Hamilton, New Zealand * @author Bernhard Pfahringer (bernhard@cs.waikato.ac.nz) * * 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 moa.classifiers.functions; import moa.classifiers.AbstractClassifier; import moa.core.Measurement; import weka.core.Instance; /** * NoChange class classifier. It always predicts the last class seen. * * @author Bernhard Pfahringer (bernhard@cs.waikato.ac.nz) * @version $Revision: 1 $ */ public class NoChange extends AbstractClassifier { private static final long serialVersionUID = 1L; @Override public String getPurposeString() { return "Weather Forecast class classifier: always predicts the last class seen."; } protected double lastSeenClass; @Override public void resetLearningImpl() { this.lastSeenClass = 0; } @Override public void trainOnInstanceImpl(Instance inst) { this.lastSeenClass = inst.classValue(); } public double[] getVotesForInstance(Instance i) { double[] votes = new double[i.numClasses()]; votes[(int) lastSeenClass] = 1.0; return votes; } @Override protected Measurement[] getModelMeasurementsImpl() { return null; } @Override public void getModelDescription(StringBuilder out, int indent) { } public boolean isRandomizable() { return false; } }