Examples of weka.core.Instance.classIndex()

weka.core.Instance.classIndex()
Returns the class attribute's index. @return the class index as an integer @throws UnassignedDatasetException if instance doesn't have access to a dataset

    m_dataLegend.addElement("RMSE");
        }
      }
      if (!inst.isMissing(inst.classIndex())) {
        double update;
        if (!inst.isMissing(inst.classIndex())) {
    update = m_eval.rootMeanSquaredError();
        } else {
    update = pred;
        }
        m_dataPoint[0] = update;

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    m_min = update;
        }
      }
      
      m_ce.setLegendText(m_dataLegend);
      m_ce.setMin((inst.isMissing(inst.classIndex()) 
       ? m_min
       : 0)); 
      m_ce.setMax(m_max);
      m_ce.setDataPoint(m_dataPoint);
      m_ce.setReset(m_reset);

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            textTitle.length());
        String results = "=== Performance information ===\n\n"
    +  "Scheme:   " + textTitle + "\n"
    +  "Relation: "+ inst.dataset().relationName() + "\n\n"
    + m_eval.toSummaryString();
              if (inst.classIndex() >= 0 && 
                  inst.classAttribute().isNominal() &&
                  (m_outputInfoRetrievalStats)) {
                results += "\n" + m_eval.toClassDetailsString();
              }

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                  inst.classAttribute().isNominal() &&
                  (m_outputInfoRetrievalStats)) {
                results += "\n" + m_eval.toClassDetailsString();
              }


              if (inst.classIndex() >= 0 && 
                  inst.classAttribute().isNominal()) {
                results += "\n" + m_eval.toMatrixString();
              }
        textTitle = "Results: " + textTitle;
        TextEvent te =

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    java.util.Enumeration enumInsts = instances.enumerateInstances();
    while (enumInsts.hasMoreElements()) 
      {
  instance = (Instance) enumInsts.nextElement();
  classIndex = (int)instance.value(instance.classIndex());
  docsPerClass[classIndex] += instance.weight();
    
  for(int a = 0; a<instance.numValues(); a++)
    if(instance.index(a) != instance.classIndex())
      {

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  instance = (Instance) enumInsts.nextElement();
  classIndex = (int)instance.value(instance.classIndex());
  docsPerClass[classIndex] += instance.weight();
    
  for(int a = 0; a<instance.numValues(); a++)
    if(instance.index(a) != instance.classIndex())
      {
        if(!instance.isMissing(a))
    {
      numOccurences = instance.valueSparse(a) * instance.weight();
      if(numOccurences < 0)

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    instance = (Instance) enumInsts.nextElement();
    docClass = (int)instance.value(classIndex);
    //docsPerClass[docClass] += instance.weight();
    
    for(int a = 0; a<instance.numValues(); a++)
        if(instance.index(a) != instance.classIndex()) {
          if(!instance.isMissing(a)) {
            numOccurrences = instance.valueSparse(a) * instance.weight();
            if(numOccurrences < 0)
          throw new Exception("Numeric attribute"+
                                                  " values must all be greater"+

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      m_Converter = temp;


      // Process all instances
      for(int xyz=0; xyz<data.numInstances(); xyz++){
  Instance datum = data.instance(xyz);
  if (!datum.isMissing(datum.classIndex())) {
    datum.setClassValue((double)m_Converter[(int)datum.classValue()]);
  }
  push(datum);
      }
    }

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      // out of range?
      if (!m_Cols.isInRange(i))
  continue;
      
      // skip class?
      if ( (result.classIndex() == i) && (!m_IncludeClass) )
  continue;
      
      // too small?
      if (result.value(i) < m_MinThreshold) {
  if (getDebug())

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   */
  protected void checkMissing(Instances instances) throws Exception {
    for (int i = 0; i < instances.numInstances(); i++) {
      Instance ins = instances.instance(i);
      for (int j = 0; j < ins.numValues(); j++) {
        if (ins.index(j) != ins.classIndex())
          if (ins.isMissingSparse(j)) {
            throw new Exception("ERROR: KDTree can not deal with missing "
                + "values. Please run ReplaceMissingValues filter "
                + "on the dataset before passing it on to the KDTree.");
          }

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