Examples of weka.core.Instance.classIndex()

weka.core.Instance.classIndex()
Returns the class attribute's index. @return the class index as an integer @throws UnassignedDatasetException if instance doesn't have access to a dataset

            textTitle.length());
        String results = "=== Performance information ===\n\n"
    +  "Scheme:   " + textTitle + "\n"
    +  "Relation: "+ inst.dataset().relationName() + "\n\n"
    + m_eval.toSummaryString();
              if (inst.classIndex() >= 0 && 
                  inst.classAttribute().isNominal() &&
                  (m_outputInfoRetrievalStats)) {
                results += "\n" + m_eval.toClassDetailsString();
              }

View Full Code Here

                  inst.classAttribute().isNominal() &&
                  (m_outputInfoRetrievalStats)) {
                results += "\n" + m_eval.toClassDetailsString();
              }


              if (inst.classIndex() >= 0 && 
                  inst.classAttribute().isNominal()) {
                results += "\n" + m_eval.toMatrixString();
              }
        textTitle = "Results: " + textTitle;
        TextEvent te =

View Full Code Here

    PMMLClassifier classifier = (PMMLClassifier)model;
    for (int i = 0; i < test.numInstances(); i++) {
      buff.append("Actual: ");
      Instance temp = test.instance(i);
      if (temp.classAttribute().isNumeric()) {
        buff.append(temp.value(temp.classIndex()) + " ");
      } else {
        buff.append(temp.classAttribute().value((int)temp.value(temp.classIndex())) + " ");
      }
      preds = classifier.distributionForInstance(temp);
      buff.append(" Predicted: ");

View Full Code Here

      buff.append("Actual: ");
      Instance temp = test.instance(i);
      if (temp.classAttribute().isNumeric()) {
        buff.append(temp.value(temp.classIndex()) + " ");
      } else {
        buff.append(temp.classAttribute().value((int)temp.value(temp.classIndex())) + " ");
      }
      preds = classifier.distributionForInstance(temp);
      buff.append(" Predicted: ");
      for (int j = 0; j < preds.length; j++) {
        buff.append("" + preds[j] + " ");

View Full Code Here

  
    java.util.Enumeration enumInsts = instances.enumerateInstances();
    while (enumInsts.hasMoreElements()) 
      {
  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())
      {

View Full Code Here

  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)

View Full Code Here

      m_Converter = temp;


      // Process all instances
      for(int xyz=0; xyz<data.numInstances(); xyz++){
  Instance datum = data.instance(xyz);
  if (!datum.isMissing(datum.classIndex())) {
    datum.setClassValue((double)m_Converter[(int)datum.classValue()]);
  }
  push(datum);
      }
    }

View Full Code Here

              // and set the data set to the training data. This is
              // just in case this test data was loaded from a CSV file
              // with all missing values for a nominal class (in this
              // case we have no information on the legal class values
              // in the test data)
              if (tempInst.isMissing(tempInst.classIndex()) && 
                  !(classifier instanceof weka.classifiers.misc.InputMappedClassifier)) {
                tempInst = (Instance)testSet.instance(i).copy();
                tempInst.setDataset(trainSet);
              }
              double predClass =

View Full Code Here

              // and set the data set to the training data. This is
              // just in case this test data was loaded from a CSV file
              // with all missing values for a nominal class (in this
              // case we have no information on the legal class values
              // in the test data)
              if (tempInst.isMissing(tempInst.classIndex()) && 
                  !(classifier instanceof weka.classifiers.misc.InputMappedClassifier)) {
                tempInst = (Instance)testSet.instance(i).copy();
                tempInst.setDataset(trainSet);
              }

View Full Code Here

      // out of range?
      if (!m_Cols.isInRange(i))
  continue;
      
      // skip class?
      if ( (result.classIndex() == i) && (!m_IncludeClass) )
  continue;
      
      // too small?
      if (result.value(i) < m_MinThreshold) {
  if (getDebug())

View Full Code Here

0 1 2 3 4 5

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.