The Network(MultiLayerPercept) does not learn

  • yokalona

    yokalona - 2012-01-15

    I make a MultiLayerPerceptron, and than need to learn him, but he does not learn!
    I make this code:

    neuralNetwork = new MultiLayerPerceptron(new int[]{8,8,1});
        trainingSet = new TrainingSet<SupervisedTrainingElement>();

    than training set loaded from file:

       TrainingSet.createFromFile("output.txt", 8, 1, " ");

    and getting start to learn:


    when I begin to test the network - it gives the same response to any input. If you repeat the training - the answer varies, but all the same just repeated.

    "output.txt" have a 8 input {-3..3} and 1 output {0.1 .. 0.9}.

    I add all from file with code:

    Iterator<SupervisedTrainingElement> iter=TrainingSet.createFromFile("output.txt", 8, 1, " ").iterator();

    The network is trained a lot of time, even too much - after 30 minutes, I realized that nothing good happened. apparently I'm doing something wrong.
    please, tell me, what the problem?

  • Zoran Sevarac

    Zoran Sevarac - 2012-01-15

    Try normalizing inputs, they all must be all in range  or , it wont work if they are in range
    Do it with

    Also if your inputs are on  it might make sense to use Tanh as transfer function, instead default sigmoid

    Good luck!

  • yokalona

    yokalona - 2012-05-20

    Thanks a lot =)
    It works =)


Log in to post a comment.

Get latest updates about Open Source Projects, Conferences and News.

Sign up for the SourceForge newsletter:

No, thanks