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weka.attributeSelection.BestFirst Maven / Gradle / Ivy

/*
 *   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 .
 */

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

package weka.attributeSelection;

import java.io.Serializable;
import java.util.*;

import weka.core.Instances;
import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.Range;
import weka.core.RevisionHandler;
import weka.core.RevisionUtils;
import weka.core.SelectedTag;
import weka.core.Tag;
import weka.core.Utils;

/**
  
 * BestFirst:

 * 

 * Searches the space of attribute subsets by greedy hillclimbing augmented with
 * a backtracking facility. Setting the number of consecutive non-improving
 * nodes allowed controls the level of backtracking done. Best first may start
 * with the empty set of attributes and search forward, or start with the full
 * set of attributes and search backward, or start at any point and search in
 * both directions (by considering all possible single attribute additions and
 * deletions at a given point).

 * 

 * 
 * 
 *  Valid options are:
 * 

 * 
 * 
 * -P <start set>
 *  Specify a starting set of attributes.
 *  Eg. 1,3,5-7.
 * 
 * 
 * 
 * -D <0 = backward | 1 = forward | 2 = bi-directional>
 *  Direction of search. (default = 1).
 * 
 * 
 * 
 * -N <num>
 *  Number of non-improving nodes to
 *  consider before terminating search.
 * 
 * 
 * 
 * -S <num>
 *  Size of lookup cache for evaluated subsets.
 *  Expressed as a multiple of the number of
 *  attributes in the data set. (default = 1)
 * 
 * 
 
 * 
 * @author Mark Hall ([email protected]) Martin Guetlein (cashing merit of
 *         expanded nodes)
 * @version $Revision: 15519 $
 */
public class BestFirst extends ASSearch implements OptionHandler,
  StartSetHandler {

  /** for serialization */
  static final long serialVersionUID = 7841338689536821867L;

  // Inner classes
  /**
   * Class for a node in a linked list. Used in best first search.
   * 
   * @author Mark Hall ([email protected])
   **/
  public class Link2 implements Serializable, RevisionHandler {

    /** for serialization */
    static final long serialVersionUID = -8236598311516351420L;

    /* BitSet group; */
    Object[] m_data;
    double m_merit;

    /**
     * Constructor
     */
    public Link2(Object[] data, double mer) {
      // group = (BitSet)gr.clone();
      m_data = data;
      m_merit = mer;
    }

    /** Get a group */
    public Object[] getData() {
      return m_data;
    }

    @Override
    public String toString() {
      return ("Node: " + m_data.toString() + "  " + m_merit);
    }

    /**
     * Returns the revision string.
     * 
     * @return the revision
     */
    @Override
    public String getRevision() {
      return RevisionUtils.extract("$Revision: 15519 $");
    }
  }

  /**
   * Class for handling a linked list. Used in best first search. Extends the
   * Vector class.
   * 
   * @author Mark Hall ([email protected])
   **/
  public class LinkedList2 extends ArrayList {

    /** for serialization */
    static final long serialVersionUID = 3250538292330398929L;

    /** Max number of elements in the list */
    int m_MaxSize;

    // ================
    // Public methods
    // ================
    public LinkedList2(int sz) {
      super();
      m_MaxSize = sz;
    }

    /**
     * removes an element (Link) at a specific index from the list.
     * 
     * @param index the index of the element to be removed.
     **/
    public void removeLinkAt(int index) throws Exception {

      if ((index >= 0) && (index < size())) {
        remove(index);
      } else {
        throw new Exception("index out of range (removeLinkAt)");
      }
    }

    /**
     * returns the element (Link) at a specific index from the list.
     * 
     * @param index the index of the element to be returned.
     **/
    public Link2 getLinkAt(int index) throws Exception {

      if (size() == 0) {
        throw new Exception("List is empty (getLinkAt)");
      } else {
        if ((index >= 0) && (index < size())) {
          return ((get(index)));
        } else {
          throw new Exception("index out of range (getLinkAt)");
        }
      }
    }

    /**
     * adds an element (Link) to the list.
     * 
     * @param data the attribute set specification
     * @param mer the "merit" of this attribute set
     **/
    public void addToList(Object[] data, double mer) throws Exception {
      Link2 newL = new Link2(data, mer);

      if (size() == 0) {
        add(newL);
      } else {
        if (mer > (get(0)).m_merit) {
          if (size() == m_MaxSize) {
            removeLinkAt(m_MaxSize - 1);
          }

          // ----------
          add(0, newL);
        } else {
          int i = 0;
          int size = size();
          boolean done = false;

          // ------------
          // don't insert if list contains max elements an this
          // is worst than the last
          if ((size == m_MaxSize) && (mer <= get(size() - 1).m_merit)) {

          }
          // ---------------
          else {
            while ((!done) && (i < size)) {
              if (mer > (get(i)).m_merit) {
                if (size == m_MaxSize) {
                  removeLinkAt(m_MaxSize - 1);
                }

                // ---------------------
                add(i, newL);
                done = true;
              } else {
                if (i == size - 1) {
                  add(newL);
                  done = true;
                } else {
                  i++;
                }
              }
            }
          }
        }
      }
    }

    /**
     * Returns the revision string.
     * 
     * @return the revision
     */
    public String getRevision() {
      return RevisionUtils.extract("$Revision: 15519 $");
    }
  }

  // member variables
  /** maximum number of stale nodes before terminating search */
  protected int m_maxStale;

  /** 0 == backward search, 1 == forward search, 2 == bidirectional */
  protected int m_searchDirection;

  /** search direction: backward */
  protected static final int SELECTION_BACKWARD = 0;
  /** search direction: forward */
  protected static final int SELECTION_FORWARD = 1;
  /** search direction: bidirectional */
  protected static final int SELECTION_BIDIRECTIONAL = 2;
  /** search directions */
  public static final Tag[] TAGS_SELECTION = {
    new Tag(SELECTION_BACKWARD, "Backward"),
    new Tag(SELECTION_FORWARD, "Forward"),
    new Tag(SELECTION_BIDIRECTIONAL, "Bi-directional"), };

  /** holds an array of starting attributes */
  protected int[] m_starting;

  /** holds the start set for the search as a Range */
  protected Range m_startRange;

  /** does the data have a class */
  protected boolean m_hasClass;

  /** holds the class index */
  protected int m_classIndex;

  /** number of attributes in the data */
  protected int m_numAttribs;

  /** total number of subsets evaluated during a search */
  protected int m_totalEvals;

  /** for debugging */
  protected boolean m_debug;

  /** holds the merit of the best subset found */
  protected double m_bestMerit;

  /** holds the maximum size of the lookup cache for evaluated subsets */
  protected int m_cacheSize;

  /**
   * Returns a string describing this search method
   * 
   * @return a description of the search method suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String globalInfo() {
    return "BestFirst:\n\n"
      + "Searches the space of attribute subsets by greedy hillclimbing "
      + "augmented with a backtracking facility. Setting the number of "
      + "consecutive non-improving nodes allowed controls the level of "
      + "backtracking done. Best first may start with the empty set of "
      + "attributes and search forward, or start with the full set of "
      + "attributes and search backward, or start at any point and search "
      + "in both directions (by considering all possible single attribute "
      + "additions and deletions at a given point).\n";
  }

  /**
   * Constructor
   */
  public BestFirst() {
    resetOptions();
  }

  /**
   * Returns an enumeration describing the available options.
   * 
   * @return an enumeration of all the available options.
   * 
   **/
  @Override
  public Enumeration listOptions() {
    Vector newVector = new Vector(4);

    newVector.addElement(new Option("\tSpecify a starting set of attributes."
      + "\n\tEg. 1,3,5-7.", "P", 1, "-P "));
    newVector.addElement(new Option("\tDirection of search. (default = 1).",
      "D", 1, "-D <0 = backward | 1 = forward " + "| 2 = bi-directional>"));
    newVector.addElement(new Option("\tNumber of non-improving nodes to"
      + "\n\tconsider before terminating search.", "N", 1, "-N "));
    newVector.addElement(new Option(
      "\tSize of lookup cache for evaluated subsets."
        + "\n\tExpressed as a multiple of the number of"
        + "\n\tattributes in the data set. (default = 1)", "S", 1, "-S "));

    newVector.addAll(Collections.list(super.listOptions()));

    return newVector.elements();
  }

  /**
   * Parses a given list of options.
   * 

   * 
    
   * Valid options are:
   * 

   * 
   * 
   * -P <start set>
   *  Specify a starting set of attributes.
   *  Eg. 1,3,5-7.
   * 
   * 
   * 
   * -D <0 = backward | 1 = forward | 2 = bi-directional>
   *  Direction of search. (default = 1).
   * 
   * 
   * 
   * -N <num>
   *  Number of non-improving nodes to
   *  consider before terminating search.
   * 
   * 
   * 
   * -S <num>
   *  Size of lookup cache for evaluated subsets.
   *  Expressed as a multiple of the number of
   *  attributes in the data set. (default = 1)
   * 
   * 
   
   * 
   * @param options the list of options as an array of strings
   * @throws Exception if an option is not supported
   * 
   **/
  @Override
  public void setOptions(String[] options) throws Exception {
    String optionString;
    resetOptions();

    optionString = Utils.getOption('P', options);
    if (optionString.length() != 0) {
      setStartSet(optionString);
    }

    optionString = Utils.getOption('D', options);

    if (optionString.length() != 0) {
      setDirection(new SelectedTag(Integer.parseInt(optionString),
        TAGS_SELECTION));
    } else {
      setDirection(new SelectedTag(SELECTION_FORWARD, TAGS_SELECTION));
    }

    optionString = Utils.getOption('N', options);

    if (optionString.length() != 0) {
      setSearchTermination(Integer.parseInt(optionString));
    }

    optionString = Utils.getOption('S', options);
    if (optionString.length() != 0) {
      setLookupCacheSize(Integer.parseInt(optionString));
    }

    m_debug = Utils.getFlag('Z', options);

    super.setOptions(options);
  }

  /**
   * Set the maximum size of the evaluated subset cache (hashtable). This is
   * expressed as a multiplier for the number of attributes in the data set.
   * (default = 1).
   * 
   * @param size the maximum size of the hashtable
   */
  public void setLookupCacheSize(int size) {
    if (size >= 0) {
      m_cacheSize = size;
    }
  }

  /**
   * Return the maximum size of the evaluated subset cache (expressed as a
   * multiplier for the number of attributes in a data set.
   * 
   * @return the maximum size of the hashtable.
   */
  public int getLookupCacheSize() {
    return m_cacheSize;
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String lookupCacheSizeTipText() {
    return "Set the maximum size of the lookup cache of evaluated subsets. This is "
      + "expressed as a multiplier of the number of attributes in the data set. "
      + "(default = 1).";
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String startSetTipText() {
    return "Set the start point for the search. This is specified as a comma "
      + "separated list off attribute indexes starting at 1. It can include "
      + "ranges. Eg. 1,2,5-9,17.";
  }

  /**
   * Sets a starting set of attributes for the search. It is the search method's
   * responsibility to report this start set (if any) in its toString() method.
   * 
   * @param startSet a string containing a list of attributes (and or ranges),
   *          eg. 1,2,6,10-15.
   * @throws Exception if start set can't be set.
   */
  @Override
  public void setStartSet(String startSet) throws Exception {
    m_startRange.setRanges(startSet);
  }

  /**
   * Returns a list of attributes (and or attribute ranges) as a String
   * 
   * @return a list of attributes (and or attribute ranges)
   */
  @Override
  public String getStartSet() {
    return m_startRange.getRanges();
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String searchTerminationTipText() {
    return "Specify the number of consecutive non-improving nodes to allow "
      + "before terminating the search.";
  }

  /**
   * Set the numnber of non-improving nodes to consider before terminating
   * search.
   * 
   * @param t the number of non-improving nodes
   * @throws Exception if t is less than 1
   */
  public void setSearchTermination(int t) throws Exception {
    if (t < 1) {
      throw new Exception("Value of -N must be > 0.");
    }

    m_maxStale = t;
  }

  /**
   * Get the termination criterion (number of non-improving nodes).
   * 
   * @return the number of non-improving nodes
   */
  public int getSearchTermination() {
    return m_maxStale;
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String directionTipText() {
    return "Set the direction of the search.";
  }

  /**
   * Set the search direction
   * 
   * @param d the direction of the search
   */
  public void setDirection(SelectedTag d) {

    if (d.getTags() == TAGS_SELECTION) {
      m_searchDirection = d.getSelectedTag().getID();
    }
  }

  /**
   * Get the search direction
   * 
   * @return the direction of the search
   */
  public SelectedTag getDirection() {

    return new SelectedTag(m_searchDirection, TAGS_SELECTION);
  }

  /**
   * Gets the current settings of BestFirst.
   * 
   * @return an array of strings suitable for passing to setOptions()
   */
  @Override
  public String[] getOptions() {

    Vector options = new Vector();

    if (!(getStartSet().equals(""))) {
      options.add("-P");
      options.add("" + startSetToString());
    }
    options.add("-D");
    options.add("" + m_searchDirection);
    options.add("-N");
    options.add("" + m_maxStale);

    Collections.addAll(options, super.getOptions());

    return options.toArray(new String[0]);
  }

  /**
   * converts the array of starting attributes to a string. This is used by
   * getOptions to return the actual attributes specified as the starting set.
   * This is better than using m_startRanges.getRanges() as the same start set
   * can be specified in different ways from the command line---eg 1,2,3 == 1-3.
   * This is to ensure that stuff that is stored in a database is comparable.
   * 
   * @return a comma separated list of individual attribute numbers as a String
   */
  private String startSetToString() {
    StringBuffer FString = new StringBuffer();
    boolean didPrint;

    if (m_starting == null) {
      return getStartSet();
    }
    for (int i = 0; i < m_starting.length; i++) {
      didPrint = false;

      if ((m_hasClass == false) || (m_hasClass == true && i != m_classIndex)) {
        FString.append((m_starting[i] + 1));
        didPrint = true;
      }

      if (i == (m_starting.length - 1)) {
        FString.append("");
      } else {
        if (didPrint) {
          FString.append(",");
        }
      }
    }

    return FString.toString();
  }

  /**
   * returns a description of the search as a String
   * 
   * @return a description of the search
   */
  @Override
  public String toString() {
    StringBuffer BfString = new StringBuffer();
    BfString.append("\tBest first.\n\tStart set: ");

    if (m_starting == null) {
      BfString.append("no attributes\n");
    } else {
      BfString.append(startSetToString() + "\n");
    }

    BfString.append("\tSearch direction: ");

    if (m_searchDirection == SELECTION_BACKWARD) {
      BfString.append("backward\n");
    } else {
      if (m_searchDirection == SELECTION_FORWARD) {
        BfString.append("forward\n");
      } else {
        BfString.append("bi-directional\n");
      }
    }

    BfString
      .append("\tStale search after " + m_maxStale + " node expansions\n");
    BfString.append("\tTotal number of subsets evaluated: " + m_totalEvals
      + "\n");
    BfString.append("\tMerit of best subset found: "
      + Utils.doubleToString(Math.abs(m_bestMerit), 8, 3) + "\n");
    return BfString.toString();
  }

  protected void printGroup(BitSet tt, int numAttribs) {
    int i;

    for (i = 0; i < numAttribs; i++) {
      if (tt.get(i) == true) {
        System.out.print((i + 1) + " ");
      }
    }

    System.out.println();
  }

  /**
   * Searches the attribute subset space by best first search
   * 
   * @param ASEval the attribute evaluator to guide the search
   * @param data the training instances.
   * @return an array (not necessarily ordered) of selected attribute indexes
   * @throws Exception if the search can't be completed
   */
  @Override
  public int[] search(ASEvaluation ASEval, Instances data) throws Exception {
    m_totalEvals = 0;
    if (!(ASEval instanceof SubsetEvaluator)) {
      throw new Exception(ASEval.getClass().getName() + " is not a "
        + "Subset evaluator!");
    }

    if (ASEval instanceof UnsupervisedSubsetEvaluator) {
      m_hasClass = false;
    } else {
      m_hasClass = true;
      m_classIndex = data.classIndex();
    }

    SubsetEvaluator ASEvaluator = (SubsetEvaluator) ASEval;
    m_numAttribs = data.numAttributes();
    int i, j;
    int best_size = 0;
    int size = 0;
    int done;
    int sd = m_searchDirection;
    BitSet best_group, temp_group;
    int stale;
    double best_merit;
    double merit;
    boolean z;
    boolean added;
    Link2 tl;
    Hashtable lookup = new Hashtable(
      m_cacheSize * m_numAttribs);
    int insertCount = 0;
    LinkedList2 bfList = new LinkedList2(m_maxStale);
    best_merit = -Double.MAX_VALUE;
    stale = 0;
    best_group = new BitSet(m_numAttribs);

    m_startRange.setUpper(m_numAttribs - 1);
    if (!(getStartSet().equals(""))) {
      m_starting = m_startRange.getSelection();
    }
    // If a starting subset has been supplied, then initialise the bitset
    if (m_starting != null) {
      for (i = 0; i < m_starting.length; i++) {
        if ((m_starting[i]) != m_classIndex) {
          best_group.set(m_starting[i]);
        }
      }

      best_size = m_starting.length;
      m_totalEvals++;
    } else {
      if (m_searchDirection == SELECTION_BACKWARD) {
        setStartSet("1-last");
        m_starting = new int[m_numAttribs];

        // init initial subset to all attributes
        for (i = 0, j = 0; i < m_numAttribs; i++) {
          if (i != m_classIndex) {
            best_group.set(i);
            m_starting[j++] = i;
          }
        }

        best_size = m_numAttribs - 1;
        m_totalEvals++;
      }
    }

    // evaluate the initial subset
    best_merit = ASEvaluator.evaluateSubset(best_group);
    // add the initial group to the list and the hash table
    Object[] best = new Object[1];
    best[0] = best_group.clone();
    bfList.addToList(best, best_merit);
    BitSet tt = (BitSet) best_group.clone();
    String hashC = tt.toString();
    lookup.put(hashC, new Double(best_merit));

    while (stale < m_maxStale) {
      added = false;

      if (m_searchDirection == SELECTION_BIDIRECTIONAL) {
        // bi-directional search
        done = 2;
        sd = SELECTION_FORWARD;
      } else {
        done = 1;
      }

      // finished search?
      if (bfList.size() == 0) {
        stale = m_maxStale;
        break;
      }

      // copy the attribute set at the head of the list
      tl = bfList.getLinkAt(0);
      temp_group = (BitSet) (tl.getData()[0]);
      temp_group = (BitSet) temp_group.clone();
      // remove the head of the list
      bfList.removeLinkAt(0);
      // count the number of bits set (attributes)
      int kk;

      for (kk = 0, size = 0; kk < m_numAttribs; kk++) {
        if (temp_group.get(kk)) {
          size++;
        }
      }

      do {
        for (i = 0; i < m_numAttribs; i++) {
          if (sd == SELECTION_FORWARD) {
            z = ((i != m_classIndex) && (!temp_group.get(i)));
          } else {
            z = ((i != m_classIndex) && (temp_group.get(i)));
          }

          if (z) {
            // set the bit (attribute to add/delete)
            if (sd == SELECTION_FORWARD) {
              temp_group.set(i);
              size++;
            } else {
              temp_group.clear(i);
              size--;
            }

            /*
             * if this subset has been seen before, then it is already in the
             * list (or has been fully expanded)
             */
            tt = (BitSet) temp_group.clone();
            hashC = tt.toString();

            if (lookup.containsKey(hashC) == false) {
              merit = ASEvaluator.evaluateSubset(temp_group);
              m_totalEvals++;

              // insert this one in the hashtable
              if (insertCount > m_cacheSize * m_numAttribs) {
                lookup = new Hashtable(m_cacheSize
                  * m_numAttribs);
                insertCount = 0;
              }
              hashC = tt.toString();
              lookup.put(hashC, new Double(merit));
              insertCount++;
            } else {
              merit = lookup.get(hashC).doubleValue();
            }

            // insert this one in the list
            Object[] add = new Object[1];
            add[0] = tt.clone();
            bfList.addToList(add, merit);

            if (m_debug) {
              System.out.print("Group: ");
              printGroup(tt, m_numAttribs);
              System.out.println("Merit: " + merit);
            }

            // is this better than the best?
            if (sd == SELECTION_FORWARD) {
              z = ((merit - best_merit) > 0.00001);
            } else {
              if (merit == best_merit) {
                z = (size < best_size);
              } else {
                z = (merit > best_merit);
              }
            }

            if (z) {
              added = true;
              stale = 0;
              best_merit = merit;
              // best_size = (size + best_size);
              best_size = size;
              best_group = (BitSet) (temp_group.clone());
            }

            // unset this addition(deletion)
            if (sd == SELECTION_FORWARD) {
              temp_group.clear(i);
              size--;
            } else {
              temp_group.set(i);
              size++;
            }
          }
        }

        if (done == 2) {
          sd = SELECTION_BACKWARD;
        }

        done--;
      } while (done > 0);

      /*
       * if we haven't added a new attribute subset then full expansion of this
       * node hasen't resulted in anything better
       */
      if (!added) {
        stale++;
      }
    }

    m_bestMerit = best_merit;
    return attributeList(best_group);
  }

  /**
   * Reset options to default values
   */
  protected void resetOptions() {
    m_maxStale = 5;
    m_searchDirection = SELECTION_FORWARD;
    m_starting = null;
    m_startRange = new Range();
    m_classIndex = -1;
    m_totalEvals = 0;
    m_cacheSize = 1;
    m_debug = false;
  }

  /**
   * converts a BitSet into a list of attribute indexes
   * 
   * @param group the BitSet to convert
   * @return an array of attribute indexes
   **/
  protected int[] attributeList(BitSet group) {
    int count = 0;

    // count how many were selected
    for (int i = 0; i < m_numAttribs; i++) {
      if (group.get(i)) {
        count++;
      }
    }

    int[] list = new int[count];
    count = 0;

    for (int i = 0; i < m_numAttribs; i++) {
      if (group.get(i)) {
        list[count++] = i;
      }
    }

    return list;
  }

  /**
   * Returns the revision string.
   * 
   * @return the revision
   */
  @Override
  public String getRevision() {
    return RevisionUtils.extract("$Revision: 15519 $");
  }
}