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.
   */
  
  /*
   *    ConditionalEstimator.java
   *    Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.estimators;
  
  import weka.core.RevisionHandler;
  
   
  /** 
   * Interface for conditional probability estimators. Example code: <p>
   *
   * <code> <pre>
   *   NNConditionalEstimator newEst = new NNConditionalEstimator();
   *
   *   // Create 50 random points and add them
   *   Random r = new Random(seed);
   *   for(int i = 0; i < 50; i++) {
   *     int x = Math.abs(r.nextInt() % 100);
   *     int y = Math.abs(r.nextInt() % 100);
   *     System.out.println("# " + x + "  " + y);
   *     newEst.addValue(x, y, 1);
   *   }
   *
   *   // Pick a random conditional value
   *   int cond = Math.abs(r.nextInt() % 100);
   *   System.out.println("## Conditional = " + cond);
   *
   *   // Print the probabilities conditional on that value
   *   Estimator result = newEst.getEstimator(cond);
   *   for(int i = 0; i <= 100; i+= 5) {
   *     System.out.println(" " + i + "  " + result.getProbability(i));
   *   }
   * </pre> </code>
   *
   * @author Len Trigg (trigg@cs.waikato.ac.nz)
   * @version $Revision: 1.7 $
   */
  public interface ConditionalEstimator extends RevisionHandler {
  
    /**
     * Add a new data value to the current estimator.
     *
     * @param data the new data value 
     * @param given the new value that data is conditional upon 
     * @param weight the weight assigned to the data value 
     */
    void addValue(double data, double given, double weight);
  
    /**
     * Get a probability estimator for a value
     *
     * @param given the new value that data is conditional upon 
     * @return the estimator for the supplied value given the condition
     */
    Estimator getEstimator(double given);
  
    /**
     * Get a probability for a value conditional on another value
     *
     * @param data the value to estimate the probability of
     * @param given the new value that data is conditional upon 
     * @return the estimator for the supplied value given the condition
     */
    double getProbability(double data, double given);
  
  }
  
  
  
  
  
  
  
  
  