Package weka.core

Examples of weka.core.Instance.numValues()

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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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    }

    // 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();
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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();
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      }
     
      // Update weight vector to reflect change a1 and a2, if linear SVM
      if (m_KernelIsLinear) {
  Instance inst1 = m_data.instance(i1);
  for (int p1 = 0; p1 < inst1.numValues(); p1++) {
    if (inst1.index(p1) != m_data.classIndex()) {
      m_weights[inst1.index(p1)] +=
        y1 * (a1 - alph1) * inst1.valueSparse(p1);
    }
  }
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      m_weights[inst1.index(p1)] +=
        y1 * (a1 - alph1) * inst1.valueSparse(p1);
    }
  }
  Instance inst2 = m_data.instance(i2);
  for (int p2 = 0; p2 < inst2.numValues(); p2++) {
    if (inst2.index(p2) != m_data.classIndex()) {
      m_weights[inst2.index(p2)] +=
        y2 * (a2 - alph2) * inst2.valueSparse(p2);
    }
  }
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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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  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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