Package weka.core

Examples of weka.core.Attribute.numValues()

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      Attribute attr = (Attribute) attrEnum.nextElement();
      if (!attr.equals(getInputFormat().classAttribute())) {
  if (attr.isNominal() || attr.isString()) {
    double[][] vdm = new double[attr.numValues()][attr.numValues()];
    vdmMap.put(attr, vdm);
    int[] featureValueCounts = new int[attr.numValues()];
    int[][] featureValueCountsByClass = new int[getInputFormat().classAttribute().numValues()][attr.numValues()];
    instanceEnum = getInputFormat().enumerateInstances();
    while(instanceEnum.hasMoreElements()) {
      Instance instance = (Instance) instanceEnum.nextElement();
      int value = (int) instance.value(attr);
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      if (!attr.equals(getInputFormat().classAttribute())) {
  if (attr.isNominal() || attr.isString()) {
    double[][] vdm = new double[attr.numValues()][attr.numValues()];
    vdmMap.put(attr, vdm);
    int[] featureValueCounts = new int[attr.numValues()];
    int[][] featureValueCountsByClass = new int[getInputFormat().classAttribute().numValues()][attr.numValues()];
    instanceEnum = getInputFormat().enumerateInstances();
    while(instanceEnum.hasMoreElements()) {
      Instance instance = (Instance) instanceEnum.nextElement();
      int value = (int) instance.value(attr);
      int classValue = (int) instance.classValue();
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      int value = (int) instance.value(attr);
      int classValue = (int) instance.classValue();
      featureValueCounts[value]++;
      featureValueCountsByClass[classValue][value]++;
    }
    for (int valueIndex1 = 0; valueIndex1 < attr.numValues(); valueIndex1++) {
      for (int valueIndex2 = 0; valueIndex2 < attr.numValues(); valueIndex2++) {
        double sum = 0;
        for (int classValueIndex = 0; classValueIndex < getInputFormat().numClasses(); classValueIndex++) {
    double c1i = (double) featureValueCountsByClass[classValueIndex][valueIndex1];
    double c2i = (double) featureValueCountsByClass[classValueIndex][valueIndex2];
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      int classValue = (int) instance.classValue();
      featureValueCounts[value]++;
      featureValueCountsByClass[classValue][value]++;
    }
    for (int valueIndex1 = 0; valueIndex1 < attr.numValues(); valueIndex1++) {
      for (int valueIndex2 = 0; valueIndex2 < attr.numValues(); valueIndex2++) {
        double sum = 0;
        for (int classValueIndex = 0; classValueIndex < getInputFormat().numClasses(); classValueIndex++) {
    double c1i = (double) featureValueCountsByClass[classValueIndex][valueIndex1];
    double c2i = (double) featureValueCountsByClass[classValueIndex][valueIndex2];
    double c1 = (double) featureValueCounts[valueIndex1];
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      } else if (attr.isDate()) {
        double dif = nnArray[nn].value(attr) - instanceI.value(attr);
        double gap = rand.nextDouble();
        values[attr.index()] = (long) (instanceI.value(attr) + gap * dif);
      } else {
        int[] valueCounts = new int[attr.numValues()];
        int iVal = (int) instanceI.value(attr);
        valueCounts[iVal]++;
        for (int nnEx = 0; nnEx < nearestNeighbors; nnEx++) {
    int val = (int) nnArray[nnEx].value(attr);
    valueCounts[val]++;
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    int val = (int) nnArray[nnEx].value(attr);
    valueCounts[val]++;
        }
        int maxIndex = 0;
        int max = Integer.MIN_VALUE;
        for (int index = 0; index < attr.numValues(); index++) {
    if (valueCounts[index] > max) {
      max = valueCounts[index];
      maxIndex = index;
    }
        }
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    double [][] avgClassValues = new double[getInputFormat().numAttributes()][0];
    m_Indices = new int[getInputFormat().numAttributes()][0];
    for (int j = 0; j < getInputFormat().numAttributes(); j++) {
      Attribute att = getInputFormat().attribute(j);
      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))) {
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    m_Indices = new int[getInputFormat().numAttributes()][0];
    for (int j = 0; j < getInputFormat().numAttributes(); j++) {
      Attribute att = getInputFormat().attribute(j);
      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();
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    }
  }
  sum = Utils.sum(avgClassValues[j]);
  totalCounts = Utils.sum(counts);
  if (Utils.gr(totalCounts, 0)) {
    for (int k = 0; k < att.numValues(); k++) {
      if (Utils.gr(counts[k], 0)) {
        avgClassValues[j][k] /= (double)counts[k];
      } else {
        avgClassValues[j][k] = sum / (double)totalCounts;
      }
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      Attribute att = getInputFormat().attribute(j);
      if ((!att.isNominal()) ||
    (j == getInputFormat().classIndex())) {
  newAtts.addElement(att.copy());
      } else {
  if ( (att.numValues() <= 2) && (!m_TransformAll) ) {
    if (m_Numeric) {
      newAtts.addElement(new Attribute(att.name()));
    } else {
      newAtts.addElement(att.copy());
    }
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