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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 .
 */

/*
 *    BatchClassifierEvent.java
 *    Copyright (C) 2002-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.gui.beans;

import java.util.EventObject;

import weka.classifiers.Classifier;

/**
 * Class encapsulating a built classifier and a batch of instances to test on.
 * 
 * @author Mark Hall
 * @version $Revision: 9263 $
 * @since 1.0
 * @see EventObject
 */
public class BatchClassifierEvent extends EventObject {

  /** for serialization */
  private static final long serialVersionUID = 878097199815991084L;

  /**
   * The classifier
   */
  protected Classifier m_classifier;
  // protected Instances m_trainingSet;

  /**
   * Instances that can be used for testing the classifier
   */
  // protected Instances m_testSet;
  protected DataSetEvent m_testSet;

  /**
   * Instances that were used to train the classifier (may be null if not
   * available)
   */
  protected DataSetEvent m_trainSet;

  /**
   * The run number that this classifier was generated for
   */
  protected int m_runNumber = 1;

  /**
   * The maximum number of runs
   */
  protected int m_maxRunNumber = 1;

  /**
   * The set number for the test set
   */
  protected int m_setNumber;

  /**
   * The last set number for this series
   */
  protected int m_maxSetNumber;

  /**
   * An identifier that can be used to group all related runs/sets together.
   */
  protected long m_groupIdentifier = Long.MAX_VALUE;

  /**
   * Label for this event
   */
  protected String m_eventLabel = "";

  /**
   * Creates a new BatchClassifierEvent instance.
   * 
   * @param source the source object
   * @param scheme a Classifier
   * @param trsI the training instances used to train the classifier
   * @param tstI the test instances
   * @param setNum the set number of the test instances
   * @param maxSetNum the last set number in the series
   */
  public BatchClassifierEvent(Object source, Classifier scheme,
      DataSetEvent trsI, DataSetEvent tstI, int setNum, int maxSetNum) {
    super(source);
    // m_trainingSet = trnI;
    m_classifier = scheme;
    m_testSet = tstI;
    m_trainSet = trsI;
    m_setNumber = setNum;
    m_maxSetNumber = maxSetNum;
  }

  /**
   * Creates a new BatchClassifierEvent instance.
   * 
   * @param source the source object
   * @param scheme a Classifier
   * @param trsI the training instances used to train the classifier
   * @param tstI the test instances
   * @param runNum the run number
   * @param maxRunNum the maximum run number
   * @param setNum the set number of the test instances
   * @param maxSetNum the last set number in the series
   */
  public BatchClassifierEvent(Object source, Classifier scheme,
      DataSetEvent trsI, DataSetEvent tstI, int runNum, int maxRunNum,
      int setNum, int maxSetNum) {

    this(source, scheme, trsI, tstI, setNum, maxSetNum);

    m_runNumber = runNum;
    m_maxRunNumber = maxRunNum;
  }

  /**
   * Set the label for this event.
   * 
   * @param lab the label to use
   */
  public void setLabel(String lab) {
    m_eventLabel = lab;
  }

  /**
   * Get the label for this event
   * 
   * @return the label for this event
   */
  public String getLabel() {
    return m_eventLabel;
  }

  /**
   * Get the classifier
   * 
   * @return the classifier
   */
  public Classifier getClassifier() {
    return m_classifier;
  }

  /**
   * Set the classifier
   * 
   * @param classifier the classifier
   */
  public void setClassifier(Classifier classifier) {
    m_classifier = classifier;
  }

  /**
   * Set the test set
   * 
   * @param tse the test set
   */
  public void setTestSet(DataSetEvent tse) {
    m_testSet = tse;
  }

  /**
   * Get the test set
   * 
   * @return the test set
   */
  public DataSetEvent getTestSet() {
    return m_testSet;
  }

  /**
   * Set the training set
   * 
   * @param tse the training set
   */
  public void setTrainSet(DataSetEvent tse) {
    m_trainSet = tse;
  }

  /**
   * Get the train set
   * 
   * @return the training set
   */
  public DataSetEvent getTrainSet() {
    return m_trainSet;
  }

  /**
   * Get the run number.
   * 
   * @return the run number
   */
  public int getRunNumber() {
    return m_runNumber;
  }

  /**
   * Get the maximum run number
   * 
   * @return the maximum run number
   */
  public int getMaxRunNumber() {
    return m_maxRunNumber;
  }

  /**
   * 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;
  }

  public void setGroupIdentifier(long identifier) {
    m_groupIdentifier = identifier;
  }

  public long getGroupIdentifier() {
    return m_groupIdentifier;
  }
}