public static void showInput(double[] input) {
    showDataWithComment("\ninput: ", input);
  }

  public static void showOutput(double[] output) {
    showDataWithComment("\noutput: ", output);
  }

  public static void showTarget(double[] target) {
    showDataWithComment("target: ", target);
  }

  private static void showDataWithComment(String comment, double[] data) {
    System.out.println(comment);
    for (int i = 0; i < data.length; i++)
      System.out.print(data[i] + " ");
    System.out.println();
  }

  public static void showWeights(double[][] weightsOfInputLayer,
                                 double[][] weightsOfOutputLayer) {
    showWeightsWithComment("weights and bias of hidden layer:", weightsOfInputLayer);
    showWeightsWithComment("weights and bias of output layer:", weightsOfOutputLayer);
  }

  private static void showWeightsWithComment(String comment, double[][] weights) {
    System.out.println("\n" + comment);
    for (int i = 0; i < weights.length; i++) {
      System.out.print("neuron " + (i + 1) + ": ");
      for (int j = 0; j < weights[i].length; j++)
        System.out.print(weights[i][j] + " ");
      System.out.println();
    }
  }

} // class DisplayMachineLearning

Die Methoden bekommen alle nötigen Informationen als Parameter, die Klasse ist vollständig unabhängig von anderen Klassen. Alles Weitere ist selbsterklärend.

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