Examples of weka.core.Instances.insertAttributeAt()

weka.core.Instances.insertAttributeAt()
Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing. Shallow copies the attribute before it is inserted, and performs a deep copy of the existing attribute information. @param att the attribute to be inserted @param position the attribute's position (position starts with 0) @throws IllegalArgumentException if the given index is out of range

    }
    
    protected Classifier generateDecisionTree(AbstractClusterer clusterer, MarkovAttributeSet aset, Instances data) throws Exception {
        // We need to create a new Attribute that has the ClusterId
        Instances newData = data; // new Instances(data);
        newData.insertAttributeAt(new Attribute("ClusterId"), newData.numAttributes());
        Attribute cluster_attr = newData.attribute(newData.numAttributes()-1);
        assert(cluster_attr != null);
        assert(cluster_attr.index() > 0);
        newData.setClass(cluster_attr);

View Full Code Here

    boostData = new Instances(data);


    // Temporarily unset the class index
    boostData.setClassIndex(-1);
    boostData.deleteAttributeAt(classIndex);
    boostData.insertAttributeAt(new Attribute("'pseudo class'"), classIndex);
    boostData.setClassIndex(classIndex);
    m_NumericClassData = new Instances(boostData, 0);


    data.randomize(m_RandomInstance);

View Full Code Here

      
      // Temporarily unset the class index
      int classIndex = data.classIndex();
      boostData.setClassIndex(-1);
      boostData.deleteAttributeAt(classIndex);
      boostData.insertAttributeAt(new Attribute("'pseudo class'"), classIndex);
      boostData.setClassIndex(classIndex);
      double [][] trainFs = new double [numInstances][m_NumClasses];
      double [][] trainYs = new double [numInstances][m_NumClasses];
      for (int j = 0; j < m_NumClasses; j++) {
  for (int i = 0, k = 0; i < numInstances; i++, k++) {

View Full Code Here

    
    // Make class numeric
    Instances trainN = new Instances(train);
    trainN.setClassIndex(-1);
    trainN.deleteAttributeAt(classIndex);
    trainN.insertAttributeAt(new Attribute("'pseudo class'"), classIndex);
    trainN.setClassIndex(classIndex);
    m_NumericClassData = new Instances(trainN, 0);
    
    // Get class values
    int numInstances = train.numInstances();

View Full Code Here

                FastVector values = new FastVector();
                values.addElement("0");
                values.addElement("1");
                Attribute a = new Attribute(instances.attribute(iAttribute).name(), (FastVector) values);
                instances.deleteAttributeAt(iAttribute);
                instances.insertAttributeAt(a,iAttribute);
            }
        }
        
        for (int iInstance = 0; iInstance < bayesNet.m_Instances.numInstances(); iInstance++) {
            Instance instanceOrig = bayesNet.m_Instances.instance(iInstance);

View Full Code Here

  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;
    }
    
    /**

View Full Code Here

        sNodeName = "Copy (" + iAttempt + ") of " + sBaseName;
        iAttempt++;
      }


      Attribute att = new Attribute(sNodeName, nomStrings);
      instances.insertAttributeAt(att, instances.numAttributes());


      valueslist = selectElements(nodelist.item(iNode), "PROPERTY");
      nValues = valueslist.size();
      // generate value strings
      int nPosX = iAttempt * 10;

View Full Code Here

      Instances filtered = new Instances(toFilter, 0); 
      FastVector nominal_values = new FastVector(m_ActualClusterer.numberOfClusters());
      for (int i = 0; i < m_ActualClusterer.numberOfClusters(); i++) {
  nominal_values.addElement("cluster" + (i+1)); 
      }
      filtered.insertAttributeAt(new Attribute("cluster", nominal_values),
    filtered.numAttributes());


      setOutputFormat(filtered);
    }

View Full Code Here


    if ((m_Insert.getIndex() < 0) || 
  (m_Insert.getIndex() > getInputFormat().numAttributes())) {
      throw new IllegalArgumentException("Index out of range");
    }
    outputFormat.insertAttributeAt(newAttribute, m_Insert.getIndex());
    setOutputFormat(outputFormat);
    
    // all attributes, except index of added attribute
    // (otherwise the length of the input/output indices differ)
    Range atts = new Range(m_Insert.getSingleIndex());

View Full Code Here

    } else if (m_attributeName.compareTo("expression") != 0) {
      newAttribute = new Attribute(m_attributeName);
    } else {
      newAttribute = new Attribute(m_infixExpression);
    }
    outputFormat.insertAttributeAt(newAttribute, 
           instanceInfo.numAttributes());
    setOutputFormat(outputFormat);
    return true;
  }

View Full Code Here

0 1 2 3 4

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.