Examples of weka.core.Range

weka.core.Range
Class representing a range of cardinal numbers. The range is set by a string representation such as:
first-last 1,2,3,4
or combinations thereof. The range is internally converted from 1-based to 0-based (so methods that set or get numbers not in string format should use 0-based numbers). @author Len Trigg (trigg@cs.waikato.ac.nz) @version $Revision: 1.18 $

    for (int i = 0; i < m_Classifiers.length; i++) {
      text.append("Classifier ").append(i + 1);
      if (m_Classifiers[i] != null) {
        if ((m_ClassFilters != null) && (m_ClassFilters[i] != null)) {
    if (m_ClassFilters[i] instanceof RemoveWithValues) {
      Range range = new Range(((RemoveWithValues)m_ClassFilters[i])
            .getNominalIndices());
      range.setUpper(m_ClassAttribute.numValues());
      int[] pair = range.getSelection();
      text.append(", " + (pair[0]+1) + " vs " + (pair[1]+1));
    } else if (m_ClassFilters[i] instanceof MakeIndicator) {
      text.append(", using indicator values: ");
      text.append(((MakeIndicator)m_ClassFilters[i]).getValueRange());
    }

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    m_CompareCombo.setEnabled(true);
    m_SortCombo.setEnabled(true);
    if (ExperimenterDefaults.getSorting().length() != 0)
      setSelectedItem(m_SortCombo, ExperimenterDefaults.getSorting());


    Range generatorRange = new Range();
    if (selectedList.length() != 0) {
      try {
  generatorRange.setRanges(selectedList);
      } catch (Exception ex) {
  ex.printStackTrace();
  System.err.println(ex.getMessage());
      }
    }
    m_TTester.setResultsetKeyColumns(generatorRange);


    generatorRange = new Range();
    if (selectedListDataset.length() != 0) {
      try {
  generatorRange.setRanges(selectedListDataset);
      } catch (Exception ex) {
  ex.printStackTrace();
  System.err.println(ex.getMessage());
      }
    }

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      int [] selected = m_ResultKeyList.getSelectedIndices();
      String selectedList = "";
      for (int i = 0; i < selected.length; i++) {
  selectedList += "," + (selected[i] + 1);
      }
      Range generatorRange = new Range();
      if (selectedList.length() != 0) {
  try {
    generatorRange.setRanges(selectedList);
  } catch (Exception ex) {
    ex.printStackTrace();
    System.err.println(ex.getMessage());
  }
      }

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      int [] selected = m_DatasetKeyList.getSelectedIndices();
      String selectedList = "";
      for (int i = 0; i < selected.length; i++) {
  selectedList += "," + (selected[i] + 1);
      }
      Range generatorRange = new Range();
      if (selectedList.length() != 0) {
  try {
    generatorRange.setRanges(selectedList);
  } catch (Exception ex) {
    ex.printStackTrace();
    System.err.println(ex.getMessage());
  }
      }

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  /**
   * Swaps the keys for dataset and result.
   */
  protected void swapDatasetKeyAndResultKey() {
    int[]   tmpSelected;
    Range  tmpRange;
    
    // lists
    tmpSelected = m_DatasetKeyList.getSelectedIndices();
    m_DatasetKeyList.setSelectedIndices(m_ResultKeyList.getSelectedIndices());
    m_ResultKeyList.setSelectedIndices(tmpSelected);

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      for(int i = 0; i < m_ClassFilters.length; i++) {
        if (m_Classifiers[i] != null && m_SumOfWeights[i] > 0) {
          Instance tempInst = (Instance)inst.copy(); 
          tempInst.setDataset(m_TwoClassDataset);
          double [] current = m_Classifiers[i].distributionForInstance(tempInst);  
          Range range = new Range(((RemoveWithValues)m_ClassFilters[i])
                                  .getNominalIndices());
          range.setUpper(m_ClassAttribute.numValues());
          int[] pair = range.getSelection();
          if (m_pairwiseCoupling && inst.numClasses() > 2) {
            r[pair[0]][pair[1]] = current[0];
            n[pair[0]][pair[1]] = m_SumOfWeights[i];
          } else {
            if (current[0] > current[1]) {

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   */
  public void setAttributes(String value) {
    if (value.length() == 0)
      m_Attributes = null;
    else
      m_Attributes = new Range(value);
  }

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  }


  /** Default constructor */
  public RemoveWithValues() {


      m_Values = new Range("first-last");
      m_Values.setInvert(true);
  }

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      setResultMatrix(new ResultMatrixHTML());
    if (Utils.getFlag("significance", options))
      setResultMatrix(new ResultMatrixSignificance());


    String datasetList = Utils.getOption('D', options);
    Range datasetRange = new Range();
    if (datasetList.length() != 0) {
      datasetRange.setRanges(datasetList);
    }
    setDatasetKeyColumns(datasetRange);


    String indexStr = Utils.getOption('R', options);
    if (indexStr.length() != 0) {
      if (indexStr.equals("first")) {
  setRunColumn(0);
      } else if (indexStr.equals("last")) {
  setRunColumn(-1);
      } else {
  setRunColumn(Integer.parseInt(indexStr) - 1);
      }    
    } else {
      setRunColumn(-1);
    }


    String foldStr = Utils.getOption('F', options);
    if (foldStr.length() != 0) {
      setFoldColumn(Integer.parseInt(foldStr) - 1);
    } else {
      setFoldColumn(-1);
    }


    String sigStr = Utils.getOption('S', options);
    if (sigStr.length() != 0) {
      setSignificanceLevel((new Double(sigStr)).doubleValue());
    } else {
      setSignificanceLevel(0.05);
    }
    
    String resultsetList = Utils.getOption('G', options);
    Range generatorRange = new Range();
    if (resultsetList.length() != 0) {
      generatorRange.setRanges(resultsetList);
    }
    setResultsetKeyColumns(generatorRange);
  }

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  public void setIgnoredAttributeIndices(String rangeList) {


    if ((rangeList == null) || (rangeList.length() == 0)) {
      m_ignoreAttributesRange = null;
    } else {
      m_ignoreAttributesRange = new Range();
      m_ignoreAttributesRange.setRanges(rangeList);
    }
  }

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weka.attributeSelection.BestFirst

weka.attributeSelection.FCBFSearch

weka.attributeSelection.GeneticSearch

weka.attributeSelection.GreedyStepwise

weka.attributeSelection.LinearForwardSelection

weka.attributeSelection.RandomSearch

weka.attributeSelection.Ranker

weka.classifiers.Evaluation

weka.classifiers.evaluation.output.prediction.AbstractOutput

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