📄 exhaustivesearch.java
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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 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.
*/
/*
* ExhaustiveSearch.java
* Copyright (C) 1999 Mark Hall
*
*/
package weka.attributeSelection;
import java.util.BitSet;
import java.util.Enumeration;
import java.util.Vector;
import weka.core.Instances;
import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.Range;
import weka.core.Utils;
/**
* Class for performing an exhaustive search. <p>
*
* Valid options are: <p>
*
* -P <start set> <br>
* Specify a starting set of attributes. Eg 1,4,7-9. <p>
*
* -V <br>
* Verbose output. Output new best subsets as the search progresses. <p>
*
* @author Mark Hall (mhall@cs.waikato.ac.nz)
* @version $Revision$
*/
public class ExhaustiveSearch extends ASSearch
implements StartSetHandler, OptionHandler {
/**
* holds a starting set as an array of attributes.
*/
private int[] m_starting;
/** the start set as a Range */
private Range m_startRange;
/** the best feature set found during the search */
private BitSet m_bestGroup;
/** the merit of the best subset found */
private double m_bestMerit;
/** does the data have a class */
private boolean m_hasClass;
/** holds the class index */
private int m_classIndex;
/** number of attributes in the data */
private int m_numAttribs;
/** if true, then ouput new best subsets as the search progresses */
private boolean m_verbose;
/**
* stop after finding the first subset equal to or better than the
* supplied start set (set to true if start set is supplied).
*/
private boolean m_stopAfterFirst;
/** the number of subsets evaluated during the search */
private int m_evaluations;
/**
* Returns a string describing this search method
* @return a description of the search suitable for
* displaying in the explorer/experimenter gui
*/
public String globalInfo() {
return "ExhaustiveSearch : \n\nPerforms an exhaustive search through "
+"the space of attribute subsets starting from the empty set of "
+"attrubutes. Reports the best subset found. If a start set is "
+"supplied, the algorithm searches backward from the start point "
+"and reports the smallest subset with as good or better evaluation "
+"as the start point.\n";
}
/**
* Constructor
*/
public ExhaustiveSearch () {
resetOptions();
}
/**
* Returns an enumeration describing the available options.
* @return an enumeration of all the available options.
**/
public Enumeration listOptions () {
Vector newVector = new Vector(2);
newVector.addElement(new Option("\tSpecify a starting set of attributes."
+ "\n\tEg. 1,3,5-7."
+"\n\tIf a start point is supplied,"
+"\n\tExhaustive search stops after"
+"\n\tfinding the smallest possible subset"
+"\n\twith merit as good as or better than"
+"\n\tthe start set."
,"P",1
, "-P <start set>"));
newVector.addElement(new Option("\tOutput subsets as the search progresses."
+"\n\t(default = false)."
, "V", 0
, "-V"));
return newVector.elements();
}
/**
* Parses a given list of options.
*
* Valid options are: <p>
*
* -P <start set> <br>
* Specify a starting set of attributes. Eg 1,4,7-9. <p>
*
* -V <br>
* Verbose output. Output new best subsets as the search progresses. <p>
*
* @param options the list of options as an array of strings
* @exception Exception if an option is not supported
*
**/
public void setOptions (String[] options)
throws Exception {
String optionString;
resetOptions();
optionString = Utils.getOption('P', options);
if (optionString.length() != 0) {
setStartSet(optionString);
}
setVerbose(Utils.getFlag('V',options));
}
/**
* 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 "
+"seperated 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. "" indicates no start set.
* If a start point is supplied, Exhaustive search stops after finding
* the smallest possible subset with merit as good as or better than the
* start set. Otherwise, the search space is explored FULLY, and the
* best subset returned.
* @exception Exception if start set can't be set.
*/
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)
*/
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 verboseTipText() {
return "Print progress information. Sends progress info to the terminal "
+"as the search progresses.";
}
/**
* set whether or not to output new best subsets as the search proceeds
* @param v true if output is to be verbose
*/
public void setVerbose(boolean v) {
m_verbose = v;
}
/**
* get whether or not output is verbose
* @return true if output is set to verbose
*/
public boolean getVerbose() {
return m_verbose;
}
/**
* Gets the current settings of RandomSearch.
* @return an array of strings suitable for passing to setOptions()
*/
public String[] getOptions () {
String[] options = new String[3];
int current = 0;
if (!(getStartSet().equals(""))) {
options[current++] = "-P";
options[current++] = ""+startSetToString();
}
if (m_verbose) {
options[current++] = "-V";
}
while (current < options.length) {
options[current++] = "";
}
return options;
}
/**
* 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 seperated 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();
}
/**
* prints a description of the search
* @return a description of the search as a string
*/
public String toString() {
StringBuffer text = new StringBuffer();
text.append("\tExhaustive Search.\n\tStart set: ");
if (m_starting == null) {
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