weka.attributeSelection.GreedyStepwise java code examples

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}

/** Creates a default BestFirst */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

search(m_ASEval, null);
resetOptions();
m_doneRanking = true;
  m_calculatedNumToSelect = final_rank.length;
 } else {
  determineNumToSelectFromThreshold(final_rank);

/**
 * Set whether to search backwards instead of forwards
 * 
 * @param back true to search backwards
 */
public void setSearchBackwards(boolean back) {
 m_backward = back;
 if (m_backward) {
  setGenerateRanking(false);
 }
}

if (getSearchBackwards()) {
 options.add("-B");
if (getConservativeForwardSelection()) {
 options.add("-C");
if (!(getStartSet().equals(""))) {
 options.add("-P");
 options.add("" + startSetToString());
if (getGenerateRanking()) {
 options.add("-R");
options.add("" + getThreshold());
options.add("" + getNumToSelect());
options.add("" + getNumExecutionSlots());
if (getDebuggingOutput()) {
 options.add("-D");

public void setOptions(String[] options) throws Exception {
 String optionString;
 resetOptions();
 setSearchBackwards(Utils.getFlag('B', options));
 setConservativeForwardSelection(Utils.getFlag('C', options));
  setStartSet(optionString);
 setGenerateRanking(Utils.getFlag('R', options));
  Double temp;
  temp = Double.valueOf(optionString);
  setThreshold(temp.doubleValue());
  setNumToSelect(Integer.parseInt(optionString));
  setNumExecutionSlots(Integer.parseInt(optionString));
 setDebuggingOutput(Utils.getFlag('D', options));

GreedyStepwise fs = new GreedyStepwise();
double[][] rankres;
fs.setGenerateRanking(true);
m_ASEval.buildEvaluator(m_Instances);
fs.search(m_ASEval, m_Instances);
rankres = fs.rankedAttributes();
m_Ranking = new int[rankres.length];
for (int i = 0; i < rankres.length; i++) {

GreedyStepwise search = new GreedyStepwise();
search.setSearchBackwards(this.backwardSelection);

 resetOptions();
 m_Instances = new Instances(data, 0);
if (!(getStartSet().equals(""))) {
 m_starting = m_startRange.getSelection();
  if (m_debug) {
   System.err.print("Best subset found so far: ");
   int[] atts = attributeList(m_best_group);
   for (int a : atts) {
    System.err.print("" + (a + 1) + " ");
return attributeList(m_best_group);

public void setOptions(String[] options) throws Exception {
 String optionString;
 resetOptions();
 setSearchBackwards(Utils.getFlag('B', options));
 setConservativeForwardSelection(Utils.getFlag('C', options));
  setStartSet(optionString);
 setGenerateRanking(Utils.getFlag('R', options));
  Double temp;
  temp = Double.valueOf(optionString);
  setThreshold(temp.doubleValue());
  setNumToSelect(Integer.parseInt(optionString));
  setNumExecutionSlots(Integer.parseInt(optionString));
 setDebuggingOutput(Utils.getFlag('D', options));

if (getSearchBackwards()) {
 options.add("-B");
if (getConservativeForwardSelection()) {
 options.add("-C");
if (!(getStartSet().equals(""))) {
 options.add("-P");
 options.add("" + startSetToString());
if (getGenerateRanking()) {
 options.add("-R");
options.add("" + getThreshold());
options.add("" + getNumToSelect());
options.add("" + getNumExecutionSlots());
if (getDebuggingOutput()) {
 options.add("-D");

 resetOptions();
 m_Instances = new Instances(data, 0);
if (!(getStartSet().equals(""))) {
 m_starting = m_startRange.getSelection();
  if (m_debug) {
   System.err.print("Best subset found so far: ");
   int[] atts = attributeList(m_best_group);
   for (int a : atts) {
    System.err.print("" + (a + 1) + " ");
return attributeList(m_best_group);

/** Creates a default GreedyStepwise */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

search(m_ASEval, null);
resetOptions();
m_doneRanking = true;
  m_calculatedNumToSelect = final_rank.length;
 } else {
  determineNumToSelectFromThreshold(final_rank);

/**
 * Set whether to search backwards instead of forwards
 * 
 * @param back true to search backwards
 */
public void setSearchBackwards(boolean back) {
 m_backward = back;
 if (m_backward) {
  setGenerateRanking(false);
 }
}

/** Creates a default BestFirst */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

/** Creates a default GreedyStepwise */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

/** Creates a default GreedyStepwise */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

/** Creates a default GreedyStepwise */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

/** Creates a default GreedyStepwise */
public ASSearch getSearch() {
 return new GreedyStepwise();
}

/**
 * constructor. Sets defaults for each member varaible. Default attribute
 * evaluator is CfsSubsetEval; default search method is BestFirst.
 */
public AttributeSelection() {
 setFolds(10);
 setRanking(false);
 setXval(false);
 setSeed(1);
 setEvaluator(new CfsSubsetEval());
 setSearch(new GreedyStepwise());
 m_selectionResults = new StringBuffer();
 m_selectedAttributeSet = null;
 m_attributeRanking = null;
}

Javadoc

GreedyStepwise :

Performs a greedy forward or backward search through the space of attribute subsets. May start with no/all attributes or from an arbitrary point in the space. Stops when the addition/deletion of any remaining attributes results in a decrease in evaluation. Can also produce a ranked list of attributes by traversing the space from one side to the other and recording the order that attributes are selected.

Valid options are:

 
-C 
Use conservative forward search

 
-B 
Use a backward search instead of a 
forward one.

 
-P <start set> 
Specify a starting set of attributes. 
Eg. 1,3,5-7.

 
-R 
Produce a ranked list of attributes.

 
-T <threshold> 
Specify a theshold by which attributes 
may be discarded from the ranking. 
Use in conjuction with -R

 
-N <num to select> 
Specify number of attributes to select

 
-num-slots <int> 
The number of execution slots, for example, the number of cores in the CPU. (default 1)

 
-D 
Print debugging output

Most used methods

<init>
Constructor
search
Searches the attribute subset space by forward selection.
setGenerateRanking
Records whether the user has requested a ranked list of attributes.
setSearchBackwards
Set whether to search backwards instead of forwards
attributeList
converts a BitSet into a list of attribute indexes
determineNumToSelectFromThreshold
getConservativeForwardSelection
Gets whether conservative selection has been enabled
getDebuggingOutput
Get whether to output debugging info to the console
getGenerateRanking
Gets whether ranking has been requested. This is used by the AttributeSelection module to determine
getNumExecutionSlots
Gets the number of threads.
getNumToSelect
Gets the number of attributes to be retained.
getSearchBackwards
Get whether to search backwards

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How to useGreedyStepwise in weka.attributeSelection

Best Java code snippets using weka.attributeSelection.GreedyStepwise (Showing top 20 results out of 315)

How to use
GreedyStepwise
in
weka.attributeSelection