qualitymeasurelcv.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.measures;

import BayesianNetworks.BayesNet;
import jbnc.dataset.DatasetInt;
import jbnc.util.BNTools;
import jbnc.util.FrequencyCalc;

import java.util.Vector;

/**
 *  LCV - Local Cross Validation. Measure the quality of the bayesian network on
 *  the dataset using local cross validation (on class variable). By default
 *  10-fold 1-time cross validation will be performed.
 *
 * @author     Jarek Sacha
 * @since      June 1, 1999
 */
public class QualityMeasureLCV extends QualityMeasure {

  protected QualityMeasureLogC logC = null;
  protected Vector[
      /*
       *  cvTimes
       */
      ][
      /*
       *  cvFolds
       */
      ] testSets = null;

  protected DatasetInt trainDataset = null;
  protected DatasetInt testDataset = null;

  protected FrequencyCalc[
      /*
       *  cvTimes
       */
      ][
      /*
       *  cvFolds
       */
      ] fc = null;

  /**  Number of cross-validation folds. */
  protected int cvFolds = 10;
  /*
   *  public void setCVFolds(int cvFolds)
   *  {
   *  this.cvFolds = cvFolds;
   *  }
   */
  /**  Number of times the cross validation is repeated (averaged). */
  protected int cvTimes = 1;


  /**  Constructor for the QualityMeasureLCV object */
  public QualityMeasureLCV() {
    super();
  }


  /**
   *  Create quality measure for given a number of cross-validation folds.
   *  Number of cross-validation repetitions is set to 1.
   *
   * @param  cvFolds  Description of Parameter
   */
  public QualityMeasureLCV(int cvFolds) {
    super();
    this.cvFolds = cvFolds;
    this.cvTimes = 1;
  }


  /**
   *  Create quality measure for given a dataset and a number of
   *  cross-validation folds. Number of cross-validation repetitions is set to
   *  1.
   *
   * @param  dataset  Description of Parameter
   * @param  cvFolds  Description of Parameter
   */
  public QualityMeasureLCV(DatasetInt dataset, int cvFolds) {
    super(dataset);
    this.cvFolds = cvFolds;
    this.cvTimes = 1;
  }


  /**
   *  Create quality measure for given a number of cross-validation folds and a
   *  number of cross-validation repetitions.
   *
   * @param  cvFolds  Description of Parameter
   * @param  cvTimes  Description of Parameter
   */
  public QualityMeasureLCV(int cvFolds, int cvTimes) {
    super();
    this.cvFolds = cvFolds;
    this.cvTimes = cvTimes;
  }


  /**
   *  Create quality measure for given a dataset and a number of
   *  cross-validation folds and a number of cross-validation repetitions.
   *
   * @param  dataset  Description of Parameter
   * @param  cvFolds  Description of Parameter
   * @param  cvTimes  Description of Parameter
   */
  public QualityMeasureLCV(DatasetInt dataset, int cvFolds, int cvTimes) {
    super(dataset);
    this.cvFolds = cvFolds;
    this.cvTimes = cvTimes;
  }


  /**
   * @param  dataset  The new Dataset value
   */
  public void setDataset(DatasetInt dataset) {
    this.dataset = dataset;

    if (dataset == null) {
      logC = null;
      testSets = null;
      trainDataset = null;
      testDataset = null;
      fc = null;
      return;
    }
    jbnc.util.CVGenerator cvGenerator = new jbnc.util.CVGenerator();
    cvGenerator.setCases(dataset.cases);

    try {
      trainDataset = (DatasetInt) dataset.clone();
      testDataset = (DatasetInt) dataset.clone();
    } catch (Exception e) {
    }

    fc = new FrequencyCalc[cvTimes][cvFolds];

    Vector[] trainSets = new Vector[cvFolds];
    testSets = new Vector[cvTimes][cvFolds];
    for (int t = 0; t < cvTimes; ++t) {
      cvGenerator.generateSets(cvFolds, trainSets, testSets[t]);
      for (int f = 0; f < cvFolds; ++f) {
        trainDataset.cases = trainSets[f];
        fc[t][f] = new FrequencyCalc(trainDataset);
      }
    }

    try {
      trainDataset = (DatasetInt) dataset.clone();
      testDataset = (DatasetInt) dataset.clone();
    } catch (Exception e) {
    }

    // Prepare logC
    logC = new QualityMeasureLogC();
    logC.setUsePriors(usePriors);
    logC.setAlphaK(alphaK);
  }


  /**
   *  Gets the Name attribute of the QualityMeasureLCV object
   *
   * @return    The Name value
   */
  public String getName() {
    return "Cross-validation " + cvFolds + "-fold " + cvTimes + "-time";
  }


  /**
   *  Gets the number of cross-validation folds.
   *
   * @return    The CVFolds value
   */
  public int getCVFolds() {
    return this.cvFolds;
  }


  /**
   *  Gets the number of times the cross validation is repeated (averaged).
   *
   * @return    The CVTimes value
   */
  public int getCVTimes() {
    return this.cvTimes;
  }


  /**
   *  Description of the Method
   *
   * @param  net            Description of Parameter
   * @return                Description of the Returned Value
   * @exception  Exception  Description of Exception
   */
  public final double evaluate(BayesNet net)
      throws Exception {

    // Calculate LC measure
    double q = 0;
    for (int t = 0; t < cvTimes; ++t) {
      for (int f = 0; f < cvFolds; ++f) {
        BNTools.learnParameters(net, fc[t][f], usePriors, alphaK);

        // test
        testDataset.cases = testSets[t][f];
        logC.setDataset(testDataset);
        q += logC.evaluate(net);
      }
    }

    return q / cvTimes;
  }
  /*
   *  public void setCVTimes(int cvTimes)
   *  {
   *  this.cvTimes = cvTimes;
   *  }
   */
}