Examples of weka.classifiers.trees.adtree.ReferenceInstances

weka.classifiers.trees.adtree.ReferenceInstances
Simple class that extends the Instances class making it possible to create subsets of instances that reference their source set. Is used by ADTree to make reweighting of instances easy to manage. @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) @version $Revision: 1.5 $


    // create training set
    m_trainInstances = new Instances(instances);


    // create positive/negative subsets
    m_posTrainInstances = new ReferenceInstances(m_trainInstances,
             m_trainInstances.numInstances());
    m_negTrainInstances = new ReferenceInstances(m_trainInstances,
             m_trainInstances.numInstances());
    for (Enumeration e = m_trainInstances.enumerateInstances(); e.hasMoreElements(); ) {
      Instance inst = (Instance) e.nextElement();
      if ((int) inst.classValue() == 0)
  m_negTrainInstances.addReference(inst); // belongs in negative class

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      clone.m_trainTotalWeight = m_trainTotalWeight;


      // reconstruct pos/negTrainInstances references
      if (m_posTrainInstances != null) { 
  clone.m_posTrainInstances =
    new ReferenceInstances(m_trainInstances, m_posTrainInstances.numInstances());
  clone.m_negTrainInstances =
    new ReferenceInstances(m_trainInstances, m_negTrainInstances.numInstances());
  for (Enumeration e = clone.m_trainInstances.enumerateInstances();
       e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    try { // ignore classValue() exception
      if ((int) inst.classValue() == 0)

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      throw new Exception("Class must be nominal!");
    }


    // create training set (use LADInstance class)
    m_trainInstances =
      new ReferenceInstances(instances, instances.numInstances());
    for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
      Instance inst = (Instance) e.nextElement();
      if (!inst.classIsMissing()) {
  LADInstance adtInst = new LADInstance(inst);
  m_trainInstances.addReference(adtInst);

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      if (inst.isMissing(attIndex)) return -1;
      else if (inst.value(attIndex) == trueSplitValue) return 0;
      else return 1;
    }
    public Instances instancesDownBranch(int branch, Instances instances) {
      ReferenceInstances filteredInstances = new ReferenceInstances(instances, 1);
      if (branch == -1) {
  for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    if (inst.isMissing(attIndex)) filteredInstances.addReference(inst);
  }
      } else if (branch == 0) {
  for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    if (!inst.isMissing(attIndex) && inst.value(attIndex) == trueSplitValue)
      filteredInstances.addReference(inst);
  }
      } else {
  for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    if (!inst.isMissing(attIndex) && inst.value(attIndex) != trueSplitValue)
      filteredInstances.addReference(inst);
  }
      }
      return filteredInstances;
    }

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      if (inst.isMissing(attIndex)) return -1;
      else if (inst.value(attIndex) < splitPoint) return 0;
      else return 1;
    }
    public Instances instancesDownBranch(int branch, Instances instances) {
      ReferenceInstances filteredInstances = new ReferenceInstances(instances, 1);
      if (branch == -1) {
  for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    if (inst.isMissing(attIndex)) filteredInstances.addReference(inst);
  }
      } else if (branch == 0) {
  for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    if (!inst.isMissing(attIndex) && inst.value(attIndex) < splitPoint)
      filteredInstances.addReference(inst);
  }
      } else {
  for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    if (!inst.isMissing(attIndex) && inst.value(attIndex) >= splitPoint)
      filteredInstances.addReference(inst);
  }
      }
      return filteredInstances;
    }

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    // create training set
    m_trainInstances = new Instances(instances);


    // create positive/negative subsets
    m_posTrainInstances = new ReferenceInstances(m_trainInstances,
             m_trainInstances.numInstances());
    m_negTrainInstances = new ReferenceInstances(m_trainInstances,
             m_trainInstances.numInstances());
    for (Enumeration e = m_trainInstances.enumerateInstances(); e.hasMoreElements(); ) {
      Instance inst = (Instance) e.nextElement();
      if ((int) inst.classValue() == 0)
  m_negTrainInstances.addReference(inst); // belongs in negative class

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      clone.m_trainTotalWeight = m_trainTotalWeight;


      // reconstruct pos/negTrainInstances references
      if (m_posTrainInstances != null) { 
  clone.m_posTrainInstances =
    new ReferenceInstances(m_trainInstances, m_posTrainInstances.numInstances());
  clone.m_negTrainInstances =
    new ReferenceInstances(m_trainInstances, m_negTrainInstances.numInstances());
  for (Enumeration e = clone.m_trainInstances.enumerateInstances();
       e.hasMoreElements(); ) {
    Instance inst = (Instance) e.nextElement();
    try { // ignore classValue() exception
      if ((int) inst.classValue() == 0)

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Related Classes of weka.classifiers.trees.adtree.ReferenceInstances

weka.classifiers.trees.ADTree

weka.classifiers.trees.LADTree

weka.classifiers.trees.LADTree$TwoWayNominalSplit

weka.classifiers.trees.LADTree$TwoWayNumericSplit

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