Examples of weka.core.Instance.index()

weka.core.Instance.index()
Returns the index of the attribute stored at the given position. Just returns the given value. @param position the position @return the index of the attribute stored at the given position

      // 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);
    }
  }
  Instance inst2 = m_data.instance(i2);
  for (int p2 = 0; p2 < inst2.numValues(); p2++) {

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        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 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();
      if(numOccurences < 0)

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    {
      numOccurences = instance.valueSparse(a) * instance.weight();
      if(numOccurences < 0)
        throw new Exception("Numeric attribute values must all be greater or equal to zero.");
      wordsPerClass[classIndex] += numOccurences;
      m_probOfWordGivenClass[classIndex][instance.index(a)] += numOccurences;
    }
      } 
      }
  
    /*

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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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                                                  " values must all be greater"+
                                                  " or equal to zero.");
                                    totalWordOccurrences += numOccurrences;
            wordsPerClass[docClass] += numOccurrences;
            ocrnceOfWordInClass[docClass]
                                          [instance.index(a)] += numOccurrences;
                                    //For the time being wordweights[0][i] 
                                    //will hold the total occurrence of word
                                    // i over all classes
                                    wordWeights[0]
                                          [instance.index(a)] += numOccurrences;

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                                          [instance.index(a)] += numOccurrences;
                                    //For the time being wordweights[0][i] 
                                    //will hold the total occurrence of word
                                    // i over all classes
                                    wordWeights[0]
                                          [instance.index(a)] += numOccurrences;
                            }
                    }
        }


  //Calculating the complement class probability for all classes except 0

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  m_AvgDocLength = 0;
  for(int i=0; i<fv.size(); i++) {
    Instance inst = (Instance) fv.elementAt(i);
    double docLength = 0;
    for(int j=0; j<inst.numValues(); j++) {
      if(inst.index(j)>=firstCopy) {
        docLength += inst.valueSparse(j) * inst.valueSparse(j);
      }
    }        
    m_AvgDocLength += Math.sqrt(docLength);
  }

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  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()) {
        counts[inst.index(i)][(int)value] += inst.weight();
        counts[inst.index(i)][0] -= inst.weight();
      } else if (inst.attributeSparse(i).isNumeric()) {
        results[inst.index(i)] += inst.weight() * inst.valueSparse(i);
      }
    } else {

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