/*
* HoeffdingOptionTreeNB.java
* Copyright (C) 2007 University of Waikato, Hamilton, New Zealand
* @author Richard Kirkby (rkirkby@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 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.
*/
package tr.gov.ulakbim.jDenetX.classifiers;
import tr.gov.ulakbim.jDenetX.options.IntOption;
import weka.core.Instance;
public class HoeffdingOptionTreeNB extends HoeffdingOptionTree {
private static final long serialVersionUID = 1L;
public IntOption nbThresholdOption = new IntOption(
"nbThreshold",
'q',
"The number of instances a leaf should observe before permitting Naive Bayes.",
0, 0, Integer.MAX_VALUE);
public static class LearningNodeNB extends ActiveLearningNode {
private static final long serialVersionUID = 1L;
public LearningNodeNB(double[] initialClassObservations) {
super(initialClassObservations);
}
public double[] getClassVotes(Instance inst, HoeffdingOptionTree hot) {
if (inst.numClasses() != (this.observedClassDistribution.maxIndex() + 1)) {
this.observedClassDistribution.setArrayLength(inst.numClasses());
}
if (getWeightSeen() >= ((HoeffdingOptionTreeNB) hot).nbThresholdOption
.getValue()) {
return NaiveBayes
.doNaiveBayesPrediction(inst,
this.observedClassDistribution,
this.attributeObservers);
}
return super.getClassVotes(inst);
}
@Override
public void disableAttribute(int attIndex) {
// should not disable poor atts - they are used in NB calc
}
}
public HoeffdingOptionTreeNB() {
this.removePoorAttsOption = null;
}
@Override
protected LearningNode newLearningNode(double[] initialClassObservations) {
return new LearningNodeNB(initialClassObservations);
}
}