/*
* 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.
*/
/*
* Classifier.java
* Copyright (C) 1999 Eibe Frank, Len Trigg
*
*/
package weka.classifiers;
import java.io.Serializable;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.SerializedObject;
import weka.core.Utils;
import weka.core.OptionHandler;
import weka.core.Option;
import java.util.Vector;
import java.util.Enumeration;
/**
* Abstract classifier. All schemes for numeric or nominal prediction in
* Weka extend this class.
*
* @author Eibe Frank (eibe@cs.waikato.ac.nz)
* @author Len Trigg (trigg@cs.waikato.ac.nz)
* @version $Revision: 1.2 $
*/
public abstract class Classifier implements Cloneable, Serializable, OptionHandler {
/** Whether the classifier is run in debug mode. */
protected boolean m_Debug = false;
/**
* Generates a classifier. Must initialize all fields of the classifier
* that are not being set via options (ie. multiple calls of buildClassifier
* must always lead to the same result). Must not change the dataset
* in any way.
*
* @param data set of instances serving as training data
* @exception Exception if the classifier has not been
* generated successfully
*/
public abstract void buildClassifier(Instances data) throws Exception;
/**
* Classifies a given instance.
*
* @param instance the instance to be classified
* @return index of the predicted class as a double
* if the class is nominal, otherwise the predicted value
* @exception Exception if instance could not be classified
* successfully
*/
public abstract double classifyInstance(Instance instance) throws Exception;
/**
* Creates a new instance of a classifier given it's class name and
* (optional) arguments to pass to it's setOptions method. If the
* classifier implements OptionHandler and the options parameter is
* non-null, the classifier will have it's options set.
*
* @param classifierName the fully qualified class name of the classifier
* @param options an array of options suitable for passing to setOptions. May
* be null.
* @return the newly created classifier, ready for use.
* @exception Exception if the classifier name is invalid, or the options
* supplied are not acceptable to the classifier
*/
public static Classifier forName(String classifierName,
String [] options) throws Exception {
return (Classifier)Utils.forName(Classifier.class,
classifierName,
options);
}
/**
* Creates copies of the current classifier, which can then
* be used for boosting etc. Note that this method now uses
* Serialization to perform a deep copy, so the Classifier
* object must be fully Serializable. Any currently built model
* will now be copied as well.
*
* @param model an example classifier to copy
* @param num the number of classifiers copies to create.
* @return an array of classifiers.
* @exception Exception if an error occurs
*/
public static Classifier [] makeCopies(Classifier model,
int num) throws Exception {
if (model == null) {
throw new Exception("No model classifier set");
}
Classifier [] classifiers = new Classifier [num];
SerializedObject so = new SerializedObject(model);
for(int i = 0; i < classifiers.length; i++) {
classifiers[i] = (Classifier) so.getObject();
}
return classifiers;
}
/**
* Returns an enumeration describing the available options.
*
* @return an enumeration of all the available options.
*/
public Enumeration listOptions() {
Vector newVector = new Vector(1);
newVector.addElement(new Option(
"\tIf set, classifier is run in debug mode and\n"
+ "\tmay output additional info to the console",
"D", 0, "-D"));
return newVector.elements();
}
/**
* Parses a given list of options. Valid options are:<p>
*
* -D <br>
* If set, classifier is run in debug mode and
* may output additional info to the console.<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 {
setDebug(Utils.getFlag('D', options));
}
/**
* Gets the current settings of the Classifier.
*
* @return an array of strings suitable for passing to setOptions
*/
public String [] getOptions() {
String [] options;
if (getDebug()) {
options = new String[1];
options[0] = "-D";
} else {
options = new String[0];
}
return options;
}
/**
* Set debugging mode.
*
* @param debug true if debug output should be printed
*/
public void setDebug(boolean debug) {
m_Debug = debug;
}
/**
* Get whether debugging is turned on.
*
* @return true if debugging output is on
*/
public boolean getDebug() {
return m_Debug;
}
/**
* Returns the tip text for this property
* @return tip text for this property suitable for
* displaying in the explorer/experimenter gui
*/
public String debugTipText() {
return "If set to true, classifier may output additional info to " +
"the console.";
}
}