Examples of weka.core.Instance.classIsMissing()

weka.core.Instance.classIsMissing()
Tests if an instance's class is missing. @return true if the instance's class is missing @throws UnassignedClassException if the class is not set or the instance doesn'thave access to a dataset

    int [] classIndices = new int [getInputFormat().numClasses() + 1];
    int currentClass = 0;
    classIndices[currentClass] = 0;
    for (int i = 0; i < getInputFormat().numInstances(); i++) {
      Instance current = getInputFormat().instance(i);
      if (current.classIsMissing()) {
        for (int j = currentClass + 1; j < classIndices.length; j++) {
          classIndices[j] = i;
        }
        break;
      } else if (current.classValue() != currentClass) {

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    int[] classIndices = new int [getInputFormat().numClasses() + 1];
    int currentClass = 0;
    classIndices[currentClass] = 0;
    for (int i = 0; i < getInputFormat().numInstances(); i++) {
      Instance current = getInputFormat().instance(i);
      if (current.classIsMissing()) {
  for (int j = currentClass + 1; j < classIndices.length; j++) {
    classIndices[j] = i;
  }
  break;
      } else if (current.classValue() != currentClass) {

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          attIdx++;
        }
      }


      if (m_TransformMethod == TRANSFORMMETHOD_MINIMAX) {
        if (!bag.classIsMissing())
          max_Inst.setClassValue(bag.classValue()); //set class value
        mini_data.add(mini_Inst); 
        max_data.add(max_Inst);
      }
      else{

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          max_Inst.setClassValue(bag.classValue()); //set class value
        mini_data.add(mini_Inst); 
        max_data.add(max_Inst);
      }
      else{
        if (!bag.classIsMissing())
          newInst.setClassValue(bag.classValue()); //set class value
        newData.add(newInst);    
      }  
    }

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    Instance tempInstance;
    for(inst = 0; inst < instanceIndex.m_NumSeqInstsSet; inst++) {
      instIndex = instanceIndex.m_SequentialInstIndexes[inst];
      //get the leave-one-out instance
      tempInstance = (Instance) m_Instances.instance(instIndex);
      if (!tempInstance.classIsMissing()) {
      tempInstanceClassValue = (int)tempInstance.classValue();
      // pointer to first index of counts matrix for efficiency
      int [][] countsPointer = counts[tempInstanceClassValue];
      // Compute the counts and priors for (n-1) instances.
      for(attIndex = 0; attIndex < instanceIndex.m_NumSeqAttsSet; attIndex++) {

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    double distance, minDistance = Double.MAX_VALUE, classValue = 0;
    updateMinMax(instance);
    Enumeration enu = m_Train.enumerateInstances();
    while (enu.hasMoreElements()) {
      Instance trainInstance = (Instance) enu.nextElement();
      if (!trainInstance.classIsMissing()) {
  distance = distance(instance, trainInstance);
  if (distance < minDistance) {
    minDistance = distance;
    classValue = trainInstance.classValue();
  }

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      m_MinTarget = Double.MAX_VALUE;
      m_MaxTarget = -Double.MAX_VALUE;


      for (int i = 0; i < train.numInstances(); i++) {
        Instance currentInst = train.instance(i);
        if (!currentInst.classIsMissing()) {
          addNumericTrainClass(currentInst.classValue(), currentInst.weight());
        }
      }


      m_ClassPriors[0] = m_ClassPriorsSum = 0;

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    // Initialize counters
    double[] temp = new double[numClasses + 1];
    for (int k = 0; k < numInstances; k++) {
      Instance inst = data.instance(k);
      if (inst.classIsMissing()) {
        temp[numClasses] += inst.weight();
      } else {
        temp[(int)inst.classValue()] += inst.weight();
      }
    }

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    // Get counts
    for (int k = 0; k < numInstances; k++) {
      Instance inst = data.instance(k);
      for (int i = 0; i < inst.numValues(); i++) {
        if (inst.index(i) != classIndex) {
          if (inst.isMissingSparse(i) || inst.classIsMissing()) {
            if (!inst.isMissingSparse(i)) {
              counts[inst.index(i)][(int)inst.valueSparse(i)][numClasses] += 
                inst.weight();
              counts[inst.index(i)][0][numClasses] -= inst.weight();
            } else if (!inst.classIsMissing()) {

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          if (inst.isMissingSparse(i) || inst.classIsMissing()) {
            if (!inst.isMissingSparse(i)) {
              counts[inst.index(i)][(int)inst.valueSparse(i)][numClasses] += 
                inst.weight();
              counts[inst.index(i)][0][numClasses] -= inst.weight();
            } else if (!inst.classIsMissing()) {
              counts[inst.index(i)][data.attribute(inst.index(i)).numValues()]
                [(int)inst.classValue()] += inst.weight();
              counts[inst.index(i)][0][(int)inst.classValue()] -= 
                inst.weight();
            } else {

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