content: /*
   *    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.
   */
  
  /*
   *    Prediction.java
   *    Copyright (C) 2002 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.classifiers.evaluation;
  
  /**
   * Encapsulates a single evaluatable prediction: the predicted value plus the 
   * actual class value.
   *
   * @author Len Trigg (len@reeltwo.com)
   * @version $Revision: 5987 $
   */
  public interface Prediction {
  
    /** 
     * Constant representing a missing value. This should have the same value
     * as weka.core.Instance.MISSING_VALUE 
     */
    double MISSING_VALUE 
      = weka.core.Utils.missingValue();
  
    /** 
     * Gets the weight assigned to this prediction. This is typically the weight
     * of the test instance the prediction was made for.
     *
     * @return the weight assigned to this prediction.
     */
    double weight();
  
    /** 
     * Gets the actual class value.
     *
     * @return the actual class value, or MISSING_VALUE if no
     * prediction was made.  
     */
    double actual();
  
    /**
     * Gets the predicted class value.
     *
     * @return the predicted class value, or MISSING_VALUE if no
     * prediction was made.  
     */
    double predicted();
  
  }
  