public static void main(String [] args) {
    //NeuralNet n = new NeuralNet();

    /* First demonstrate how the layout looks with just one neuron. */
    /* Output neuron uses a linear function, f=x^(1). */
    //n.setOutputNeuron(new Neuron(new PolynomialTerm(1)));

    /* Add inputs. */
    /*for(int i = 0; i < 3; i++) {
      n.addInputNeuron(new Neuron(new PrimaryInput("Input"+i)));
    }

    int counter = 0;
    while(true) {
      if(counter%1000==0)
        System.out.println(n.getOutputNeuron());
      DataPoint dp = new DataPoint();
      double i = Math.random();
      double j = Math.random();
      dp.addFeature("Input0", i);
      dp.addFeature("Input1", j);
      dp.addFeature("Input2", 0);
      dp.setExpected(i*2+3+j);
      n.learn(dp);
      counter+=1;
    }
  */}