Examples of NeuralNode


Examples of weka.classifiers.functions.neural.NeuralNode

          , true);
      return;
    }

        }
        NeuralNode temp = new NeuralNode(String.valueOf(m_nextId),
                 m_random, m_sigmoidUnit);
        m_nextId++;
        temp.setX((double)e.getX() / w);
        temp.setY((double)e.getY() / h);
        tmp.addElement(temp);
        addNode(temp);
        selection(tmp, (e.getModifiers() & MouseEvent.CTRL_MASK) == MouseEvent.CTRL_MASK
      , true);
      }
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Examples of weka.classifiers.functions.neural.NeuralNode

      return buf.toString();
    }
   
    StringBuffer model = new StringBuffer(m_neuralNodes.length * 100);
    //just a rough size guess
    NeuralNode con;
    double[] weights;
    NeuralConnection[] inputs;
    for (int noa = 0; noa < m_neuralNodes.length; noa++) {
      con = (NeuralNode) m_neuralNodes[noa]//this would need a change
                                              //for items other than nodes!!!
      weights = con.getWeights();
      inputs = con.getInputs();
      if (con.getMethod() instanceof SigmoidUnit) {
  model.append("Sigmoid ");
      }
      else if (con.getMethod() instanceof LinearUnit) {
  model.append("Linear ");
      }
      model.append("Node " + con.getId() + "\n    Inputs    Weights\n");
      model.append("    Threshold    " + weights[0] + "\n");
      for (int nob = 1; nob < con.getNumInputs() + 1; nob++) {
  if ((inputs[nob - 1].getType() & NeuralConnection.PURE_INPUT)
      == NeuralConnection.PURE_INPUT) {
    model.append("    Attrib " +
           m_instances.attribute(((NeuralEnd)inputs[nob-1]).
               getLink()).name()
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