Examples of weka.filters.Filter

weka.filters.Filter
An abstract class for instance filters: objects that take instances as input, carry out some transformation on the instance and then output the instance. The method implementations in this class assume that most of the work will be done in the methods overridden by subclasses.
A simple example of filter use. This example doesn't remove instances from the output queue until all instances have been input, so has higher memory consumption than an approach that uses output instances as they are made available:
```
 Filter filter = ..some type of filter.. Instances instances = ..some instances.. for (int i = 0; i < data.numInstances(); i++) { filter.input(data.instance(i)); } filter.batchFinished(); Instances newData = filter.outputFormat(); Instance processed; while ((processed = filter.output()) != null) { newData.add(processed); } ..do something with newData.. 
```
@author Len Trigg (trigg@cs.waikato.ac.nz) @version $Revision: 6833 $

    m_FilterEditor.setCapabilitiesFilter(filterClass);
    
    // check capabilities
    m_ApplyFilterBut.setEnabled(true);
    Capabilities currentCapabilitiesFilter = m_FilterEditor.getCapabilitiesFilter();
    Filter currentFilter = (Filter) m_FilterEditor.getValue();
    Capabilities currentFilterCapabilities = null;
    if (currentFilter != null && currentCapabilitiesFilter != null &&
        (currentFilter instanceof CapabilitiesHandler)) {
      currentFilterCapabilities = ((CapabilitiesHandler)currentFilter).getCapabilities();

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    PointDouble      values;
    Instances      data;
    Evaluation      eval;
    PointDouble      result;
    Classifier      classifier;
    Filter      filter;
    int        size;
    boolean      cached;
    boolean      allCached;
    Performance      p1;
    Performance      p2;
    double      x;
    double      y;
    
    performances = new Vector();
    
    log("Determining best pair with " + cv + "-fold CV in Grid:\n" + grid + "\n");
    
    if (m_Traversal == TRAVERSAL_BY_COLUMN)
      size = grid.width();
    else
      size = grid.height();
    
    allCached = true;


    for (i = 0; i < size; i++) {
      if (m_Traversal == TRAVERSAL_BY_COLUMN)
  enm = grid.column(i);
      else
  enm = grid.row(i);
      
      filter = null;
      data   = null;
      
      while (enm.hasMoreElements()) {
  values = enm.nextElement();
  
  // already calculated?
  cached = m_Cache.isCached(cv, values);
  if (cached) {
    performances.add(m_Cache.get(cv, values));
  }
  else {
    allCached = false;
    
    x = evaluate(values.getX(), true);
    y = evaluate(values.getY(), false);
    
    // data pass through filter
    if (filter == null) {
      filter = (Filter) setup(getFilter(), x, y);
      filter.setInputFormat(inst);
      data = Filter.useFilter(inst, filter);
      // make sure that the numbers don't get too small - otherwise NaNs!
      Filter cleaner = new NumericCleaner();
      cleaner.setInputFormat(data);
      data = Filter.useFilter(data, cleaner);
    }


    // setup classifier
    classifier = (Classifier) setup(getClassifier(), x, y);

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   *
   * @return     the filter string.
   */
  protected String getFilterSpec() {
    String  result;
    Filter   filter;
    
    filter = getFilter();
    result = filter.getClass().getName();
    
    if (filter instanceof OptionHandler)
      result += " " + Utils.joinOptions(((OptionHandler) filter).getOptions());
    
    return result;

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   * Get the filter + options as a string
   *
   * @return a String containing the name of the filter + any options
   */
  protected String getFilterSpec() {
    Filter c = getFilter();
    if (c instanceof OptionHandler) {
      return c.getClass().getName() + " "
  + Utils.joinOptions(((OptionHandler)c).getOptions());
    }
    return c.getClass().getName();
  }

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   *
   * @return the filter string.
   */
  protected String getFilterSpec() {
    
    Filter c = getFilter();
    if (c instanceof OptionHandler) {
      return c.getClass().getName() + " "
  + Utils.joinOptions(((OptionHandler)c).getOptions());
    }
    return c.getClass().getName();
  }

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      m_filterEditor.setValue(new weka.filters.unsupervised.attribute.Add());
      m_filterEditor.addPropertyChangeListener(new PropertyChangeListener() {
    public void propertyChange(PropertyChangeEvent e) {
      repaint();
      if (m_filter != null) {
        Filter editedF = (Filter)m_filterEditor.getValue();
        m_filter.setFilter(editedF);
        // should pass on the property change to any other interested
        // listeners
      }
    }

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   *
   * @return     the filter string.
   */
  protected String getFilterSpec() {
    String  result;
    Filter   filter;
    
    filter = getFilter();
    result = filter.getClass().getName();
    
    if (filter instanceof OptionHandler)
      result += " " + Utils.joinOptions(((OptionHandler) filter).getOptions());
    
    return result;

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    double[] instanceStats = new double[cc];
    Instances testRaw = null;
    boolean hasClass = (test.classIndex() >= 0);
    int unclusteredInstances = 0;
    Vector<Double> clusterAssignments = new Vector<Double>();
    Filter filter = null;
    DataSource source = null;
    Instance inst;


    if (testFileName == null)
      testFileName = "";
    
    // load data
    if (testFileName.length() != 0)
      source = new DataSource(testFileName);
    else
      source = new DataSource(test);
    testRaw = source.getStructure(test.classIndex());
    
    // If class is set then do class based evaluation as well
    if (hasClass) {
      if (testRaw.classAttribute().isNumeric())
  throw new Exception("ClusterEvaluation: Class must be nominal!");


      filter = new Remove();
      ((Remove) filter).setAttributeIndices("" + (testRaw.classIndex() + 1));
      ((Remove) filter).setInvertSelection(false);
      filter.setInputFormat(testRaw);
    }
    
    i = 0;
    while (source.hasMoreElements(testRaw)) {
      // next instance
      inst = source.nextElement(testRaw);
      if (filter != null) {
  filter.input(inst);
  filter.batchFinished();
  inst = filter.output();
      }
      
      cnum = -1;
      try {
  if (m_Clusterer instanceof DensityBasedClusterer) {

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   * Get the filter + options as a string
   *
   * @return a String containing the name of the filter + any options
   */
  protected String getFilterSpec() {
    Filter c = getFilter();
    if (c instanceof OptionHandler) {
      return c.getClass().getName() + " "
  + Utils.joinOptions(((OptionHandler)c).getOptions());
    }
    return c.getClass().getName();
  }

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   * the filter and any options to the filter
   *
   * @return     the filter string.
   */
  protected String getFilterSpec() {
    Filter c = getFilter();
    
    if (c instanceof OptionHandler)
      return   c.getClass().getName() + " " 
             + Utils.joinOptions(((OptionHandler)c).getOptions());
    else
      return c.getClass().getName();
  }

View Full Code Here

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