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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This is the stable version. Apart from bugfixes, this version
does not receive any other updates.
/*
* 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 .
*/
/*
* BatchClustererEvent.java
* Copyright (C) 2004-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.gui.beans;
import java.util.EventObject;
import weka.clusterers.Clusterer;
/**
* Class encapsulating a built clusterer and a batch of instances to
* test on.
*
* @author Stefan Mutter
* @version $Revision: 8034 $
* @since 1.0
* @see EventObject
*/
public class BatchClustererEvent
extends EventObject {
/** for serialization */
private static final long serialVersionUID = 7268777944939129714L;
/**
* The clusterer
*/
protected Clusterer m_clusterer;
// protected Instances m_trainingSet;
/**
* Training or Test Instances
*/
// protected Instances m_testSet;
protected DataSetEvent m_testSet;
/**
* The set number for the test set
*/
protected int m_setNumber;
/**
* Indicates if m_testSet is a training or a test set. 0 for test, >0 for training
*/
protected int m_testOrTrain;
/**
* The last set number for this series
*/
protected int m_maxSetNumber;
public static int TEST = 0;
public static int TRAINING = 1;
/**
* Creates a new BatchClustererEvent
instance.
*
* @param source the source object
* @param scheme a Clusterer
* @param tstI the training/test instances
* @param setNum the set number of the training/testinstances
* @param maxSetNum the last set number in the series
* @param testOrTrain 0 if the set is a test set, >0 if it is a training set
*/
public BatchClustererEvent(Object source, Clusterer scheme, DataSetEvent tstI, int setNum, int maxSetNum, int testOrTrain) {
super(source);
// m_trainingSet = trnI;
m_clusterer = scheme;
m_testSet = tstI;
m_setNumber = setNum;
m_maxSetNumber = maxSetNum;
if(testOrTrain == 0)
m_testOrTrain = TEST;
else
m_testOrTrain = TRAINING;
}
/**
* Get the clusterer
*
* @return the clusterer
*/
public Clusterer getClusterer() {
return m_clusterer;
}
/**
* Get the training/test set
*
* @return the training/testing instances
*/
public DataSetEvent getTestSet() {
return m_testSet;
}
/**
* Get the set number (ie which fold this is)
*
* @return the set number for the training and testing data sets
* encapsulated in this event
*/
public int getSetNumber() {
return m_setNumber;
}
/**
* Get the maximum set number (ie the total number of training
* and testing sets in the series).
*
* @return the maximum set number
*/
public int getMaxSetNumber() {
return m_maxSetNumber;
}
/**
* Get whether the set of instances is a test or a training set
*
* @return 0 for test set, >0 fro training set
*/
public int getTestOrTrain(){
return m_testOrTrain;
}
}