Examples of weka.core.Instances.deleteAttributeAt()

weka.core.Instances.deleteAttributeAt()
Deletes an attribute at the given position (0 to numAttributes() - 1). A deep copy of the attribute information is performed before the attribute is deleted. @param position the attribute's position (position starts with 0) @throws IllegalArgumentException if the given index is out of rangeor the class attribute is being deleted

    protected Instances getNumericData(Instances data) throws Exception{
  Instances numericData = new Instances(data);
  
  int classIndex = numericData.classIndex();
  numericData.setClassIndex(-1);
  numericData.deleteAttributeAt(classIndex);
  numericData.insertAttributeAt(new Attribute("'pseudo class'"), classIndex);
  numericData.setClassIndex(classIndex);
  return numericData;
    }

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    /* create a new output format (multi-instance format) */
    Instances newData = instanceInfo.stringFreeStructure();
    Attribute attBagIndex = (Attribute) newData.attribute(0).copy();
    Attribute attClass = (Attribute) newData.classAttribute().copy();
    // remove the bagIndex attribute
    newData.deleteAttributeAt(0);
    // remove the class attribute
    newData.setClassIndex(-1);
    newData.deleteAttributeAt(newData.numAttributes() - 1);


    FastVector attInfo = new FastVector(3);

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    Attribute attClass = (Attribute) newData.classAttribute().copy();
    // remove the bagIndex attribute
    newData.deleteAttributeAt(0);
    // remove the class attribute
    newData.setClassIndex(-1);
    newData.deleteAttributeAt(newData.numAttributes() - 1);


    FastVector attInfo = new FastVector(3); 
    attInfo.addElement(attBagIndex);
    attInfo.addElement(new Attribute("bag", newData)); // relation-valued attribute
    attInfo.addElement(attClass);

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    Instances testData = new Instances(exmp.dataset(), 0);
    testData.add(exmp);


    // convert the training dataset into single-instance dataset
    testData = Filter.useFilter(testData, m_ConvertToProp);  
    testData.deleteAttributeAt(0); //remove the bagIndex attribute  


    if (m_Filter != null)  
      testData = Filter.useFilter(testData, m_Filter); 


    for(int j = 0; j < testData.numInstances(); j++){

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    if (getDebug())
      System.out.println("Start training ...");
    Instances data = transform(train); 


    data.deleteAttributeAt(0); // delete the bagID attribute
    m_Classifier.buildClassifier(data);


    if (getDebug())
      System.out.println("Finish building model");
  }

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    double [] distribution = new double[2];
    Instances test = new Instances (newBag.dataset(), 0);  
    test.add(newBag);  


    test = transform(test);
    test.deleteAttributeAt(0);
    Instance newInst=test.firstInstance();


    distribution = m_Classifier.distributionForInstance(newInst);


    return distribution;

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    //convert the training dataset into single-instance dataset
    m_ConvertToProp.setWeightMethod(getWeightMethod());
    m_ConvertToProp.setInputFormat(train);
    train = Filter.useFilter(train, m_ConvertToProp);
    train.deleteAttributeAt(0); // remove the bag index attribute


    m_Classifier.buildClassifier(train);
  }    


  /**

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    m_ConvertToProp.setWeightMethod(
        new SelectedTag(
          MultiInstanceToPropositional.WEIGHTMETHOD_ORIGINAL, 
          MultiInstanceToPropositional.TAGS_WEIGHTMETHOD));
    testData = Filter.useFilter(testData, m_ConvertToProp);
    testData.deleteAttributeAt(0); //remove the bag index attribute


    // Compute the log-probability of the bag
    double [] distribution = new double[m_NumClasses];
    double nI = (double)testData.numInstances();
    double [] maxPr = new double [m_NumClasses];

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  if(instances.classIndex() < 0)
            throw new Exception("For class association rule mining a class attribute has to be specified.");
  if(invert){
    for(int i=0;i<newInstances.numAttributes();i++){
        if(i!=newInstances.classIndex()){
      newInstances.deleteAttributeAt(i);
      i--;
        }
    }
      return newInstances;
  }

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    }
      return newInstances;
  }
  else{
      newInstances.setClassIndex(-1);
            newInstances.deleteAttributeAt(instances.classIndex());
      return newInstances;
  }
    }

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