Package org.neuroph.nnet.learning

Examples of org.neuroph.nnet.learning.BinaryDeltaRule


    Perceptron nnet = new Perceptron(inputNeuronsCount, outputNeuronsCount, transferFunctionType);

                if (learningRule.getName().equals(PerceptronLearning.class.getName()))  {
                    nnet.setLearningRule(new PerceptronLearning());
                } else if (learningRule.getName().equals(BinaryDeltaRule.class.getName())) {
                    nnet.setLearningRule(new BinaryDeltaRule());
                }

    return nnet;
  }
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    ConnectionFactory.fullConnect(inputLayer, outputLayer);

    // set input and output cells for this network
    NeuralNetworkFactory.setDefaultIO(this);
               
                this.setLearningRule(new BinaryDeltaRule());
    // set appropriate learning rule for this network
//    if (transferFunctionType == TransferFunctionType.STEP) {
//      this.setLearningRule(new BinaryDeltaRule(this));
//    } else if (transferFunctionType == TransferFunctionType.SIGMOID) {
//      this.setLearningRule(new SigmoidDeltaRule(this));
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