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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.

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/*
 *   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 3 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, see .
 */

/*
 *    EntropyBasedSplitCrit.java
 *    Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers.trees.j48;

import weka.core.ContingencyTables;

/**
 * "Abstract" class for computing splitting criteria
 * based on the entropy of a class distribution.
 *
 * @author Eibe Frank ([email protected])
 * @version $Revision: 10055 $
 */
public abstract class EntropyBasedSplitCrit
  extends SplitCriterion {

  /** for serialization */
  private static final long serialVersionUID = -2618691439791653056L;

  /**
   * Help method for computing entropy.
   */
  public final double lnFunc(double num) {

    // Constant hard coded for efficiency reasons
    if (num < 1e-6)
      return 0;
    else
      return ContingencyTables.lnFunc(num);
  }

  /**
   * Computes entropy of distribution before splitting.
   */
  public final double oldEnt(Distribution bags) {

    double returnValue = 0;
    int j;

    for (j=0;j