Package weka.core

Examples of weka.core.Instance.numValues()

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  while (enumInsts.hasMoreElements()) {
    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"+
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  sums[i] = sumOfWeights;
      }
      double[] results = new double[getInputFormat().numAttributes()];
      for (int j = 0; j < getInputFormat().numInstances(); j++) {
  Instance inst = getInputFormat().instance(j);
  for (int i = 0; i < inst.numValues(); i++) {
    if (!inst.isMissingSparse(i)) {
      double value = inst.valueSparse(i);
      if (inst.attributeSparse(i).isNominal()) {
              if (counts[inst.index(i)].length > 0) {
                counts[inst.index(i)][(int)value] += inst.weight();
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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();
 
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      double temp_diffP_diffA_givNearest =
        difference(m_classIndex, inst.value(m_classIndex),
                   cmp.value(m_classIndex));
      // now the attributes
      for (int p1 = 0, p2 = 0;
           p1 < inst.numValues() || p2 < cmp.numValues();) {
        if (p1 >= inst.numValues()) {
          firstI = m_trainInstances.numAttributes();
        } else {
          firstI = inst.index(p1);
        }
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        if (p1 >= inst.numValues()) {
          firstI = m_trainInstances.numAttributes();
        } else {
          firstI = inst.index(p1);
        }
        if (p2 >= cmp.numValues()) {
          secondI = m_trainInstances.numAttributes();
        } else {
          secondI = cmp.index(p2);
        }
        if (firstI == m_trainInstances.classIndex()) {
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        ? m_trainInstances.
        instance((int)m_karray[cl][tempSortedClass[j]][1])
        : m_trainInstances.instance((int)m_karray[cl][j][1]);

      for (int p1 = 0, p2 = 0;
           p1 < inst.numValues() || p2 < cmp.numValues();) {
        if (p1 >= inst.numValues()) {
          firstI = m_trainInstances.numAttributes();
        } else {
          firstI = inst.index(p1);
        }
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        if (p1 >= inst.numValues()) {
          firstI = m_trainInstances.numAttributes();
        } else {
          firstI = inst.index(p1);
        }
        if (p2 >= cmp.numValues()) {
          secondI = m_trainInstances.numAttributes();
        } else {
          secondI = cmp.index(p2);
        }
        if (firstI == m_trainInstances.classIndex()) {
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              ? m_trainInstances.
              instance((int)m_karray[k][tempSortedAtt[k][j]][1])
              : m_trainInstances.instance((int)m_karray[k][j][1]);
       
            for (int p1 = 0, p2 = 0;
                 p1 < inst.numValues() || p2 < cmp.numValues();) {
              if (p1 >= inst.numValues()) {
                firstI = m_trainInstances.numAttributes();
              } else {
                firstI = inst.index(p1);
              }
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              if (p1 >= inst.numValues()) {
                firstI = m_trainInstances.numAttributes();
              } else {
                firstI = inst.index(p1);
              }
              if (p2 >= cmp.numValues()) {
                secondI = m_trainInstances.numAttributes();
              } else {
                secondI = cmp.index(p2);
              }
              if (firstI == m_trainInstances.classIndex()) {
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      System.out.format("Warning: zero or negative weights in JS calculation! (pi1 %s, pi2 %s)\n", pi1, pi2);
      return 0;
    }
    Instance inst = m_data.instance(instIdx);
    double kl1 = 0.0, kl2 = 0.0, tmp = 0.0;   
    for (int i = 0; i < inst.numValues(); i++) {
      tmp = input.Py_x.get(inst.index(i), instIdx);     
      if(tmp != 0) {
  kl1 += tmp * Math.log(tmp / (tmp * pi1 + pi2 * T.Py_t.get(inst.index(i), t)));
      }
    }
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