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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.

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/*
 *   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 .
 */

/*
 * NaiveBayes.java
 * Copyright (C) 2004-2012 University of Waikato, Hamilton, New Zealand
 * 
 */
package weka.classifiers.bayes.net.search.fixed;

import weka.classifiers.bayes.BayesNet;
import weka.classifiers.bayes.net.search.SearchAlgorithm;
import weka.core.Instances;
import weka.core.RevisionUtils;

/** 
 
 * The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables.
 * 

* * * @author Remco Bouckaert * @version $Revision: 8034 $ */ public class NaiveBayes extends SearchAlgorithm { /** for serialization */ static final long serialVersionUID = -4808572519709755811L; /** * Returns a string describing this object * @return a description of the classifier suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "The NaiveBayes class generates a fixed Bayes network structure " + "with arrows from the class variable to each of the attribute " + "variables."; } /** * * @param bayesNet * @param instances the instances to work with * @throws Exception if something goes wrong */ public void buildStructure (BayesNet bayesNet, Instances instances) throws Exception { for (int iAttribute = 0; iAttribute < instances.numAttributes(); iAttribute++) { if (iAttribute != instances.classIndex()) { bayesNet.getParentSet(iAttribute).addParent(instances.classIndex(), instances); } } } // buildStructure /** * Returns the revision string. * * @return the revision */ public String getRevision() { return RevisionUtils.extract("$Revision: 8034 $"); } } // class NaiveBayes





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