Examples of weka.core.Instances.numInstances()

weka.core.Instances.numInstances()
Returns the number of instances in the dataset. @return the number of instances in the dataset as an integer

        if ( data.attribute(i).isNominal() ) 
          numNominal++;
        if ( data.attribute(i).isNumeric() ) 
          numNumeric++;
      }
      System.err.printf( "%s\t%d\t%d\t%d\t%d\t", curArff.getName(), data.numInstances(), numNumeric, numNominal, data.numClasses() );
     


      /* We have adopted a generalization of AUC score to multiclass problems as
       * described in Provost and Domingos (CeDER Working Paper #IS-00-04, Stern
       * School of Business, New York University, 2001), computed by taking a

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       * School of Business, New York University, 2001), computed by taking a
       * weighted average over all one-vs-all binary classification problems
       * that can be derived from the multiclass problem, where weights
       * correspond to class prior probabilities. */
      double[] classProps = new double[data.numClasses()];
      for ( int i = 0; i < data.numInstances(); i++ )
        classProps[ (int) data.instance(i).classValue() ] += data.instance(i).weight();
      Utils.normalize(classProps);


      double[][] aucScore = new double[classifiers.length][numRuns];
      double[][] accyScore = new double[classifiers.length][numRuns];

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          //Run the model creation
          Instances filter_training_set = Filter.useFilter(data, filter);
          
          //emit the instances used to train the filter
          for(int i=0; i<filter_training_set.numInstances(); i++){
            collector.emit(new Values(filter_training_set.get(i)));
          }
          
          training = false;
          //Empty the queue for memories

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      try{
          if(!m_DataBaseConnection.isConnected())
              connectToDatabase();
          setWriteMode(WRITE);
          writeStructure();
          for(int i = 0; i < instances.numInstances(); i++){
            writeInstance(instances.instance(i));
          }
          m_DataBaseConnection.disconnectFromDatabase();
          setWriteMode(WAIT);
          resetStructure();

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        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++){
        double pred = cls.classifyInstance(data.instance(i));
        ClusterClass clusClass = ClusterClass.valueOf(
            data.classAttribute().value((int)pred).toUpperCase());
        if(!retval.containsKey(clusClass)){
          retval.put(clusClass, new ArrayList<StoredDomainCluster>());

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    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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    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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    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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    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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    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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