Examples of FastVector


Examples of weka.core.FastVector

    int[] m_nPosX;

    int[] m_nPosY;

    public DeleteSelectionAction(FastVector nodes) {
      m_nodes = new FastVector();
      int nNodes = nodes.size();
      m_att = new Attribute[nNodes];
      m_CPT = new Estimator[nNodes][];
      m_ParentSet = new ParentSet[nNodes];
      m_nPosX = new int[nNodes];
      m_nPosY = new int[nNodes];
      m_deleteArcActions = new FastVector();
      for (int iNode = 0; iNode < nodes.size(); iNode++) {
        int nTargetNode = (Integer) nodes.elementAt(iNode);
        m_nodes.addElement(nTargetNode);
        m_att[iNode] = m_Instances.attribute(nTargetNode);
        try {
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Examples of weka.core.FastVector

    Estimator[][] m_CPT;

    AddArcAction(int nParent, int nChild) {
      try {
        m_nParent = nParent;
        m_children = new FastVector();
        m_children.addElement(nChild);
        //m_nChild = nChild;
        SerializedObject so = new SerializedObject(m_Distributions[nChild]);
        m_CPT = new Estimator[1][];
        m_CPT[0] = (Estimator[]) so.getObject();
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Examples of weka.core.FastVector

    } // c'tor

    AddArcAction(int nParent, FastVector children) {
      try {
        m_nParent = nParent;
        m_children = new FastVector();
        m_CPT = new Estimator[children.size()][];
        for (int iChild = 0; iChild < children.size(); iChild++) {
          int nChild = (Integer) children.elementAt(iChild);
          m_children.addElement(nChild);
          SerializedObject so = new SerializedObject(m_Distributions[nChild]);
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Examples of weka.core.FastVector

            return -2;
        }
    }

    private Instances initializeDataSet(int numFeatures, int neededCapacity) {
        FastVector fvAllAttributes = new FastVector(numFeatures + 1);
        Attribute tempAtt;
        for (int i = 0; i < numFeatures; i++) {
            tempAtt = new Attribute("att" + i);
            fvAllAttributes.addElement(tempAtt);
        }
        FastVector fvClassVal = new FastVector(2);
        fvClassVal.addElement("positive");
        fvClassVal.addElement("negative");
        Attribute ClassAttribute = new Attribute("theClass", fvClassVal);
        fvAllAttributes.addElement(ClassAttribute);
        // Create an empty training set
        Instances emptySet = new Instances("dataSet", fvAllAttributes, neededCapacity);
        emptySet.setClassIndex(numFeatures);
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