List of classIsMissing() Examples

Examples of 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

Examples of weka.core.Instance.classIsMissing()

      Assert.assertEquals("REL statechum compatibility score",testClassifier.attributesOfAnInstance[1].name());
    }
    
    {// pairB - another correct pair
      Instance instance = instEnum.nextElement();
      Assert.assertFalse(instance.classIsMissing());Assert.assertEquals(5,instance.numValues());
      Assert.assertFalse(instance.hasMissingValue());
      Assert.assertTrue(instance.classAttribute().isNominal());
      Assert.assertEquals(2,instance.classAttribute().numValues());// true/false
      Assert.assertEquals("true",instance.classAttribute().value((int) instance.value(instance.classAttribute())));

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Examples of weka.core.Instance.classIsMissing()

      Assert.assertEquals("REL statechum compatibility score",testClassifier.attributesOfAnInstance[1].name());
    }
    
    {// pairC - incorrect pair
      Instance instance = instEnum.nextElement();
      Assert.assertFalse(instance.classIsMissing());Assert.assertEquals(5,instance.numValues());
      Assert.assertFalse(instance.hasMissingValue());
      Assert.assertTrue(instance.classAttribute().isNominal());
      Assert.assertEquals(2,instance.classAttribute().numValues());// true/false
      Assert.assertEquals("false",instance.classAttribute().value((int) instance.value(instance.classAttribute())));

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Examples of weka.core.Instance.classIsMissing()

  double sumWeightedXDiffSquared = 0;
  double sumWeightedYDiffSquared = 0;
  m_slope = 0;
  for (int j = 0; j < insts.numInstances(); j++) {
    Instance inst = insts.instance(j);
    if (!inst.isMissing(i) && !inst.classIsMissing()) {
      double xDiff = inst.value(i) - xMean;
      double yDiff = inst.classValue() - yMean;
      double weightedXDiff = inst.weight() * xDiff;
      double weightedYDiff = inst.weight() * yDiff;
      m_slope += weightedXDiff * yDiff;

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Examples of weka.core.Instance.classIsMissing()

    m_K = 0;
  out:
    for (int it = 0; it < m_NumIterations; it++) {
      for (int i = 0; i < m_Train.numInstances(); i++) {
  Instance inst = m_Train.instance(i);
  if (!inst.classIsMissing()) {
    int prediction = makePrediction(m_K, inst);
    int classValue = (int) inst.classValue();
    if (prediction == classValue) {
      m_Weights[m_K]++;
    } else {

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Examples of weka.core.Instance.classIsMissing()

    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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Examples of weka.core.Instance.classIsMissing()

    int [] counts = new int [getInputFormat().numClasses()];
    double [] weights = new double [getInputFormat().numClasses()];
    int min = -1;
    for (int i = 0; i < getInputFormat().numInstances(); i++) {
      Instance current = getInputFormat().instance(i);
      if (current.classIsMissing() == false) {
        counts[(int)current.classValue()]++;
        weights[(int)current.classValue()]+= current.weight();
      }
    }

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Examples of weka.core.Instance.classIsMissing()

    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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Examples of weka.core.Instance.classIsMissing()

      if (att.isNominal()) {
  avgClassValues[j] = new double [att.numValues()];
  counts = new double [att.numValues()];
  for (int i = 0; i < getInputFormat().numInstances(); i++) {
    instance = getInputFormat().instance(i);
    if (!instance.classIsMissing() && 
        (!instance.isMissing(j))) {
      counts[(int)instance.value(j)] += instance.weight();
      avgClassValues[j][(int)instance.value(j)] += 
        instance.weight() * instance.classValue();
    }

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Examples of weka.core.Instance.classIsMissing()

      m_PriorErrorEstimator = null;
      m_ErrorEstimator = null;


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

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Examples of weka.core.Instance.classIsMissing()

        instancesOfClass[ i ] = new Instances( data, 0 );
      }
      Enumeration enu = data.enumerateInstances();
      while( enu.hasMoreElements() ) {
        Instance instance = (Instance)enu.nextElement();
        if( instance.classIsMissing() ) {
          instancesOfClass[numClasses].add( instance );
  }
  else {
          int c = (int)instance.classValue();
          instancesOfClass[c].add( instance );

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