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.
   */
  
  /*
   *    IterativeClassifier.java
   *    Copyright (C) 2001  University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.classifiers;
  
  import weka.core.*;
  
  /**
   * Interface for classifiers that can induce models of growing
   * complexity one step at a time.
   *
   * @author Gabi Schmidberger (gabi@cs.waikato.ac.nz)
   * @author Bernhard Pfahringer (bernhard@cs.waikato.ac.nz)
   * @version $Revision: 6041 $
   */
  
  public interface IterativeClassifier {
  
    /**
     * Inits an iterative classifier.
     *
     * @param instances the instances to be used in induction
     * @exception Exception if the model cannot be initialized
     */
    void initClassifier(Instances instances) throws Exception;
  
    /**
     * Performs one iteration.
     *
     * @param iteration the index of the current iteration (0-based)
     * @exception Exception if this iteration fails
     */
    void next(int iteration) throws Exception;
  
    /**
     * Signal end of iterating, useful for any house-keeping/cleanup
     *
     * @exception Exception if cleanup fails
     */
    void done() throws Exception;
  
    /**
      * Performs a deep copy of the classifier, and a reference copy
      * of the training instances (or a deep copy if required).
      *
      * @return a clone of the classifier
      */
    Object clone() throws CloneNotSupportedException;
  
  }
  