Package weka.core

Examples of weka.core.Instances.numAttributes()

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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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    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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    //////////////////////////////////////////////////////////////////////////////////////////
    //fill all matrix data to weka data
    for( Integer i = 1; i < u.m; i++ ) {
      double[] vals = new double[data.numAttributes()];
       for( Integer j = 0; j < u.n; j++) {
         strName = u.A[0][j].getData();
         strTemp = u.A[i][j].getData();
         ArrayList<String> values = mapValues.get(strName);
         vals[j] = values.indexOf(strTemp);
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    //////////////////////////////////////////////////////////////////////////////////////////
    //fill all matrix data to weka data
    for( Unit s : ships.list ){
       for( Integer t = 0; t < RDB.This().getTime(); t++ ){
         double[] vals = new double[data.numAttributes()];
           
         int j = 0;
          for( String strAtrribute : attributeList){
            Unit c = s.get(strAtrribute);
            ArrayList<String> values =  mapValues.get(strAtrribute);
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    //////////////////////////////////////////////////////////////////////////////////////////
    //fill all TDB data to weka data
    for( Integer t = 0; t < RDB.This().getTime(); t++ ){
      int i = 0;
      double[] vals = new double[data.numAttributes()];
      for( String strName: mapUnit.keySet() ){
        Unit u = mapUnit.get(strName);
        ArrayList<String> values = mapValues.get(strName);
        String strData = u.getLastDataByTime(t);
       
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      // add
      data.add(new DenseInstance(1.0, vals));  
    }
   
    //2.4. set class attribute
      data.setClassIndex(data.numAttributes() - 3);
   
    System.out.println("");
    System.out.println(data);
       
    return data;
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    System.out.println("Filtered data:"+data);
   
    /*
     * Remove score attribute
     */
    data.deleteAttributeAt(data.numAttributes() - 2);
    System.out.println("Filtered data:"+data);
   
    //set class attribute
    data.setClassIndex(data.numAttributes()-1);
   
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     */
    data.deleteAttributeAt(data.numAttributes() - 2);
    System.out.println("Filtered data:"+data);
   
    //set class attribute
    data.setClassIndex(data.numAttributes()-1);
   
    /*
     * build J48 classifier
     */
    classifier.buildClassifier(data);
 
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    discretize.setInputFormat(data);
    data = Filter.useFilter(data, discretize);
    //System.out.println("Filtered data:"+data);
   
    //set class attribute
    data.setClassIndex(data.numAttributes()-1);
    discretizedDataset.setDataset(data);
   
    /*
     * build J48 classifier
     */
 
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