/*
* 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.
*/
/*
* VisualizeBayesNet.java
* Copyright (C) 2009 University of Waikato, Hamilton, New Zealand
*/
package wekaexamples.gui.graphvisualizer;
import weka.classifiers.bayes.BayesNet;
import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;
import weka.gui.graphvisualizer.GraphVisualizer;
import java.awt.BorderLayout;
import javax.swing.JFrame;
/**
* Displays a trained BayesNet graph.
* Expects an ARFF filename as first argument.
*
* @author FracPete (fracpete at waikato dot ac dot nz)
* @version $Revision$
*/
public class VisualizeBayesNet {
/**
* Expects an ARFF file as first parameter (class attribute is assumed to
* be the last attribute).
*
* @param args the commandline arguments
* @throws Exception if something goes wrong
*/
public static void main(String args[]) throws Exception {
// train classifier
BayesNet cls = new BayesNet();
Instances data = DataSource.read(args[0]);
data.setClassIndex(data.numAttributes() - 1);
cls.buildClassifier(data);
// display graph
GraphVisualizer gv = new GraphVisualizer();
gv.readBIF(cls.graph());
JFrame jf = new JFrame("BayesNet graph");
jf.setDefaultCloseOperation(JFrame.DISPOSE_ON_CLOSE);
jf.setSize(800, 600);
jf.getContentPane().setLayout(new BorderLayout());
jf.getContentPane().add(gv, BorderLayout.CENTER);
jf.setVisible(true);
// layout graph
gv.layoutGraph();
}
}