Examples of deleteAttributeAt()


Examples of weka.core.Instances.deleteAttributeAt()

    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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Examples of weka.core.Instances.deleteAttributeAt()

    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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Examples of weka.core.Instances.deleteAttributeAt()

    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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Examples of weka.core.Instances.deleteAttributeAt()

    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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Examples of weka.core.Instances.deleteAttributeAt()

    //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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Examples of weka.core.Instances.deleteAttributeAt()

    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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Examples of weka.core.Instances.deleteAttributeAt()

  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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Examples of weka.core.Instances.deleteAttributeAt()

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

  
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Examples of weka.core.Instances.deleteAttributeAt()

      while (lastInstance < originalDataSet.numInstances()
    && sequenceID == originalDataSet.instance(lastInstance).value(dataSeqID)) {
  lastInstance++;
      }
      Instances dataSequence = new Instances(originalDataSet, firstInstance, (lastInstance)-firstInstance);
      dataSequence.deleteAttributeAt(dataSeqID);
      dataSequences.addElement(dataSequence);
      firstInstance = lastInstance;
    }
    return dataSequences;
  }
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Examples of weka.core.Instances.deleteAttributeAt()

    FastVector dataSequences = extractDataSequences(m_OriginalDataSet, m_DataSeqID);
    long minSupportCount = Math.round(m_MinSupport * dataSequences.size());
    FastVector kMinusOneSequences;
    FastVector kSequences;

    originalDataSet.deleteAttributeAt(0);
    FastVector oneElements = Element.getOneElements(originalDataSet);
    m_Cycles = 1;

    kSequences = Sequence.oneElementsToSequences(oneElements);
    Sequence.updateSupportCount(kSequences, dataSequences);
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