/*
* M5P.java
* Copyright (C) 2001 Mark Hall
*
* 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 weka.classifiers.trees.m5;
import java.io.*;
import java.util.*;
import weka.core.*;
/**
* M5P. Implements routines for generating M5 model trees.
*
* Valid options are:<p>
*
* -U <br>
* Use unsmoothed predictions. <p>
*
* @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a>
* @version $Revision: 1.1.1.1 $
*/
public class M5P extends M5Base
implements Drawable {
/**
* Creates a new <code>M5P</code> instance.
*/
public M5P() {
super();
setGenerateRules(false);
}
/**
* Return a dot style String describing the tree.
*
* @return a <code>String</code> value
* @exception Exception if an error occurs
*/
public String graph() throws Exception {
StringBuffer text = new StringBuffer();
text.append("digraph M5Tree {\n");
Rule temp = (Rule)m_ruleSet.elementAt(0);
temp.m_topOfTree.graph(text);
text.append("}\n");
return text.toString();
}
/**
* Set whether to save instance data at each node in the
* tree for visualization purposes
*
* @param save a <code>boolean</code> value
*/
public void setSaveInstances(boolean save) {
m_saveInstances = save;
}
/**
* Get whether instance data is being save.
*
* @return a <code>boolean</code> value
*/
public boolean getSaveInstances() {
return m_saveInstances;
}
/**
* Returns an enumeration describing the available options
*
* @return an enumeration of all the available options
*/
public Enumeration listOptions() {
Enumeration superOpts = super.listOptions();
Vector newVector = new Vector();
while (superOpts.hasMoreElements()) {
newVector.addElement((Option)superOpts.nextElement());
}
newVector.addElement(new Option("\tSave instances at the nodes in\n"
+"\tthe tree (for visualization purposes)\n",
"L", 0, "-L"));
return newVector.elements();
}
/**
* Parses a given list of options. <p>
*
* Valid options are:<p>
*
* -U <br>
* Use unsmoothed predictions. <p>
*
* -R <br>
* Build a regression tree rather than a model tree. <p>
*
* -L <br>
* Save instance data at each node (for visualization purposes). <p>
*
* @param options the list of options as an array of strings
* @exception Exception if an option is not supported
*/
public void setOptions(String[] options) throws Exception {
setSaveInstances(Utils.getFlag('L', options));
super.setOptions(options);
}
/**
* Gets the current settings of the classifier.
*
* @return an array of strings suitable for passing to setOptions
*/
public String [] getOptions() {
String[] superOpts = super.getOptions();
String [] options = new String [superOpts.length+1];
int current = superOpts.length;
for (int i = 0; i < current; i++) {
options[i] = superOpts[i];
}
if (getSaveInstances()) {
options[current++] = "-L";
}
while (current < options.length) {
options[current++] = "";
}
return options;
}
/**
* Main method by which this class can be tested
*
* @param args an array of options
*/
public static void main(String[] args) {
try {
System.out.println(weka.classifiers.Evaluation.evaluateModel(
new M5P(),
args));
} catch (Exception e) {
System.err.println(e.getMessage());
e.printStackTrace();
}
}
}