Package weka.core

Examples of weka.core.Instances.numAttributes()

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        new HashMap<ClusterClass, List<StoredDomainCluster>>();
    try{
      DataSource source = new DataSource(new ByteArrayInputStream(prepfeatures.getBytes()));
      Instances data = source.getDataSet();
      if (data.classIndex() == -1){
        data.setClassIndex(data.numAttributes() - 1);
      }
      String[] options = weka.core.Utils.splitOptions("-p 0");
      J48 cls = (J48)weka.core.SerializationHelper.read(modelfile);
      cls.setOptions(options);
      for(int i = 0; i < data.numInstances(); i++){
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    Reader arffReader = null;
    try
    {
      arffReader = new FileReader(arffWithTrainingData);
      Instances trainingData = new Instances(arffReader);
      if (!"class".equals(trainingData.attribute(trainingData.numAttributes()-1).name()))
        throw new IllegalArgumentException("last element is not a class");
      trainingData.setClassIndex(trainingData.numAttributes()-1);
     
      classifier.buildClassifier(trainingData);
    }
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    {
      arffReader = new FileReader(arffWithTrainingData);
      Instances trainingData = new Instances(arffReader);
      if (!"class".equals(trainingData.attribute(trainingData.numAttributes()-1).name()))
        throw new IllegalArgumentException("last element is not a class");
      trainingData.setClassIndex(trainingData.numAttributes()-1);
     
      classifier.buildClassifier(trainingData);
    }
    catch(Exception ex)
    {// we cannot proceed if this happens because every classifier should be able to both learn and deliver. Throw the exception.
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    FastVector attributes = new FastVector(attributeNumber);attributes.addElement(attrA);attributes.addElement(attrB);attributes.addElement(attrC);attributes.addElement(attrClass);
    Instances trainingData = new Instances("trainingdata",attributes,10);// this assigns indices to attributes, without these indices I cannot create instances.
    trainingData.setClassIndex(attrClass.index());
    Instance inst = new Instance(attributeNumber);
    inst.setValue(attrA,0);inst.setValue(attrB, 1);inst.setValue(attrC, 1);inst.setValue(attrClass, 0);
    Assert.assertEquals(4,trainingData.numAttributes());
    Assert.assertEquals(0,trainingData.numInstances());
    trainingData.add(inst);
    Assert.assertEquals(4,trainingData.numAttributes());
    Assert.assertEquals(1,trainingData.numInstances());
  }
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    Instance inst = new Instance(attributeNumber);
    inst.setValue(attrA,0);inst.setValue(attrB, 1);inst.setValue(attrC, 1);inst.setValue(attrClass, 0);
    Assert.assertEquals(4,trainingData.numAttributes());
    Assert.assertEquals(0,trainingData.numInstances());
    trainingData.add(inst);
    Assert.assertEquals(4,trainingData.numAttributes());
    Assert.assertEquals(1,trainingData.numInstances());
  }
 
  @Test
  public void testConstructTooBig1()
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    Reader arffReader = null;
    try
    {
      arffReader = new FileReader(arffWithTrainingData);
      Instances trainingData = new Instances(arffReader);
      if (!"class".equals(trainingData.attribute(trainingData.numAttributes()-1).name()))
        throw new IllegalArgumentException("last element is not a class");
      trainingData.setClassIndex(trainingData.numAttributes()-1);
     
      classifier.buildClassifier(trainingData);
    }
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    {
      arffReader = new FileReader(arffWithTrainingData);
      Instances trainingData = new Instances(arffReader);
      if (!"class".equals(trainingData.attribute(trainingData.numAttributes()-1).name()))
        throw new IllegalArgumentException("last element is not a class");
      trainingData.setClassIndex(trainingData.numAttributes()-1);
     
      classifier.buildClassifier(trainingData);
    }
    catch(Exception ex)
    {// we cannot proceed if this happens because every classifier should be able to both learn and deliver. Throw the exception.
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    Reader arffReader = null;
    try
    {
      arffReader = new FileReader(arffWithTrainingData);
      Instances trainingData = new Instances(arffReader);
      if (!"class".equals(trainingData.attribute(trainingData.numAttributes()-1).name()))
        throw new IllegalArgumentException("last element is not a class");
      trainingData.setClassIndex(trainingData.numAttributes()-1);
     
      classifier.buildClassifier(trainingData);
    }
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    {
      arffReader = new FileReader(arffWithTrainingData);
      Instances trainingData = new Instances(arffReader);
      if (!"class".equals(trainingData.attribute(trainingData.numAttributes()-1).name()))
        throw new IllegalArgumentException("last element is not a class");
      trainingData.setClassIndex(trainingData.numAttributes()-1);
     
      classifier.buildClassifier(trainingData);
    }
    catch(Exception ex)
    {// we cannot proceed if this happens because every classifier should be able to both learn and deliver. Throw the exception.
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    FastVector attributes = new FastVector(attributeNumber);attributes.addElement(attrA);attributes.addElement(attrB);attributes.addElement(attrC);attributes.addElement(attrClass);
    Instances trainingData = new Instances("trainingdata",attributes,10);// this assigns indices to attributes, without these indices I cannot create instances.
    trainingData.setClassIndex(attrClass.index());
    Instance inst = new Instance(attributeNumber);
    inst.setValue(attrA,0);inst.setValue(attrB, 1);inst.setValue(attrC, 1);inst.setValue(attrClass, 0);
    Assert.assertEquals(4,trainingData.numAttributes());
    Assert.assertEquals(0,trainingData.numInstances());
    trainingData.add(inst);
    Assert.assertEquals(4,trainingData.numAttributes());
    Assert.assertEquals(1,trainingData.numInstances());
  }
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