Package weka.core

Examples of weka.core.FastVector.addElement()


    classAt = m_Instances.attribute(m_ClassIndex);
    if (classAt.isNominal()) {
      attVals = new FastVector();
      for (i = 0; i < classAt.numValues(); i++)
  attVals.addElement(classAt.value(i));
      predictedClass = new Attribute("predicted" + classAt.name(), attVals);
    }
    else {
      predictedClass = new Attribute("predicted" + classAt.name());
    }
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    }
   
    // create new header
    atts = new FastVector();
    for (i = 0; i < m_PlotInstances.numAttributes(); i++)
      atts.addElement(m_PlotInstances.attribute(i));
    for (i = 0; i < maxNum; i++) {
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-lowerBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-upperBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-width"));
    }
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    // create new header
    atts = new FastVector();
    for (i = 0; i < m_PlotInstances.numAttributes(); i++)
      atts.addElement(m_PlotInstances.attribute(i));
    for (i = 0; i < maxNum; i++) {
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-lowerBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-upperBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-width"));
    }
    data = new Instances(m_PlotInstances.relationName(), atts, m_PlotInstances.numInstances());
    data.setClassIndex(m_PlotInstances.classIndex());
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    atts = new FastVector();
    for (i = 0; i < m_PlotInstances.numAttributes(); i++)
      atts.addElement(m_PlotInstances.attribute(i));
    for (i = 0; i < maxNum; i++) {
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-lowerBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-upperBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-width"));
    }
    data = new Instances(m_PlotInstances.relationName(), atts, m_PlotInstances.numInstances());
    data.setClassIndex(m_PlotInstances.classIndex());
   
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    for (i = 0; i < m_PlotInstances.numAttributes(); i++)
      atts.addElement(m_PlotInstances.attribute(i));
    for (i = 0; i < maxNum; i++) {
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-lowerBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-upperBoundary"));
      atts.addElement(new Attribute("predictionInterval_" + (i+1) + "-width"));
    }
    data = new Instances(m_PlotInstances.relationName(), atts, m_PlotInstances.numInstances());
    data.setClassIndex(m_PlotInstances.classIndex());
   
    // update data
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      for (int i=0; i<insts.numClasses(); i++) {
  for (int j=0; j<insts.numClasses(); j++) {
    if (j<=i) continue;
    int[] pair = new int[2];
    pair[0] = i; pair[1] = j;
    pairs.addElement(pair);
  }
      }

      numClassifiers = pairs.size();
      m_Classifiers = AbstractClassifier.makeCopies(m_Classifier, numClassifiers);
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      m_TwoClassDataset = new Instances(insts, 0);
      int classIndex = m_TwoClassDataset.classIndex();
      m_TwoClassDataset.setClassIndex(-1);
      m_TwoClassDataset.deleteAttributeAt(classIndex);
      FastVector classLabels = new FastVector();
      classLabels.addElement("class0");
      classLabels.addElement("class1");
      m_TwoClassDataset.insertAttributeAt(new Attribute("class", classLabels),
            classIndex);
      m_TwoClassDataset.setClassIndex(classIndex);
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      int classIndex = m_TwoClassDataset.classIndex();
      m_TwoClassDataset.setClassIndex(-1);
      m_TwoClassDataset.deleteAttributeAt(classIndex);
      FastVector classLabels = new FastVector();
      classLabels.addElement("class0");
      classLabels.addElement("class1");
      m_TwoClassDataset.insertAttributeAt(new Attribute("class", classLabels),
            classIndex);
      m_TwoClassDataset.setClassIndex(classIndex);

    } else { // use error correcting code style methods
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      if (m_CreateSparseData) {
  newInst = new SparseInstance(1.0, vals);
      } else {
  newInst = new DenseInstance(1.0, vals);
      }
      instances.addElement(newInst);
      rowCount++;
    }
    //disconnectFromDatabase();  (perhaps other queries might be made)
   
    // Create the header and add the instances to the dataset
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      /* Fix for databases that uppercase column names */
      // String attribName = attributeCaseFix(md.getColumnName(i + 1));
      String attribName = attributeCaseFix(columnNames.get(i));
      switch (attributeTypes[i]) {
      case Attribute.NOMINAL:
  attribInfo.addElement(new Attribute(attribName, nominalStrings[i]));
  break;
      case Attribute.NUMERIC:
  attribInfo.addElement(new Attribute(attribName));
  break;
      case Attribute.STRING:
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