frequencytable.java

bayes network classifier toolbox 贝叶斯网络分类工具箱

/**
 *  JBNC - Bayesian Network Classifiers Toolbox <p>
 *
 *  Latest release available at http://sourceforge.net/projects/jbnc/ <p>
 *
 *  Copyright (C) 1999-2003 Jarek Sacha <p>
 *
 *  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. <p>
 *
 *  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. <p>
 *
 *  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., 59 Temple
 *  Place - Suite 330, Boston, MA 02111-1307, USA. <br>
 *  http://www.fsf.org/licenses/gpl.txt
 */
package jbnc.util;

import BayesianNetworks.BayesNet;
import BayesianNetworks.ProbabilityFunction;

import java.util.Vector;

/**
 *  Description of the Class
 *
 * @author     Jarek Sacha
 * @since      June 1, 1999
 */
public final class FrequencyTable {

  protected int nbCases = 0;
  protected FrequencyNode[] frequencyNodes;


  /**
   *  Constructor for the FrequencyTable object
   *
   * @param  net  Description of Parameter
   */
  public FrequencyTable(BayesNet net) {
    ProbabilityFunction[] funcs = net.get_probability_functions();

    frequencyNodes = new FrequencyNode[funcs.length];
    for (int i = 0; i < frequencyNodes.length; ++i) {
      frequencyNodes[i] = new FrequencyNode(funcs[i]);
    }
  }


  /**
   *  Sets the Cases attribute of the FrequencyTable object
   *
   * @param  cases  The new Cases value
   */
  public void setCases(Vector cases) {
    removeAllCases();
    int nbCases = cases.size();
    for (int c = 0; c < nbCases; ++c) {
      int[] thisCase = (int[]) cases.get(c);
      for (int i = 0; i < frequencyNodes.length; ++i) {
        frequencyNodes[i].addCase(thisCase);
      }
    }

    this.nbCases = nbCases;
  }


  /**
   *  Gets the N attribute of the FrequencyTable object
   *
   * @param  i  Description of Parameter
   * @param  j  Description of Parameter
   * @param  k  Description of Parameter
   * @return    The N value
   */
  public int getN(int i, int j, int k) {
    return frequencyNodes[i].nJK[j][k];
  }


  /**
   *  Gets the N attribute of the FrequencyTable object
   *
   * @param  i  Description of Parameter
   * @param  j  Description of Parameter
   * @return    The N value
   */
  public int getN(int i, int j) {
    return frequencyNodes[i].nJ[j];
  }


  /**
   *  Gets the NbCases attribute of the FrequencyTable object
   *
   * @return    The NbCases value
   */
  public int getNbCases() {
    return nbCases;
  }


  /**
   *  Adds a feature to the Case attribute of the FrequencyTable object
   *
   * @param  aCase  The feature to be added to the Case attribute
   */
  public void addCase(int[] aCase) {
    for (int i = 0; i < frequencyNodes.length; ++i) {
      frequencyNodes[i].addCase(aCase);
    }

    ++nbCases;
  }


  /**
   *  Description of the Method
   *
   * @param  aCase          Description of Parameter
   * @exception  Exception  Description of Exception
   */
  public void removeCase(int[] aCase) throws Exception {
    if (nbCases < 1) {
      throw new Exception("No cases to remove from.");
    }

    for (int i = 0; i < frequencyNodes.length; ++i) {
      frequencyNodes[i].removeCase(aCase);
    }

    --nbCases;
  }


  /**  Description of the Method */
  public void removeAllCases() {
    nbCases = 0;
    if (frequencyNodes != null) {
      for (int i = 0; i < frequencyNodes.length; ++i) {
        frequencyNodes[i].removeAllCases();
      }
    }
  }


  /**
   *  Description of the Method
   *
   * @param  net            Description of Parameter
   * @param  usePriors      Description of Parameter
   * @param  alphaK         Description of Parameter
   * @exception  Exception  Description of Exception
   */
  public void learnNetParam(BayesNet net,
                            boolean usePriors,
                            double alphaK) throws Exception {
    // Sanity checks
    if (usePriors && (alphaK <= 0)) {
      throw new Exception("When using Dirihlet priors alphaK must be greater than zero.");
    }

    if (frequencyNodes.length != net.number_variables()) {
      throw new Exception("Number of variables in the data set and in the network do no agree ("
          + frequencyNodes.length + "!=" + net.number_variables() + ").");
    }

    // Iterate through the list of probability functions
    // and calculate new values using frequencies in the training dataset.
    ProbabilityFunction[] funcs = net.get_probability_functions();
    for (int funcNb = 0; funcNb < funcs.length; ++funcNb) {
      if (funcs[funcNb] == null) {
        continue;
      }

      double[] vals = funcs[funcNb].get_values();

      frequencyNodes[funcNb].learnNodeParam(vals, usePriors, alphaK);
    }

  }
}