Package org.encog.neural.pattern

Examples of org.encog.neural.pattern.ElmanPattern.generate()

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    ElmanPattern pattern = new ElmanPattern();
    pattern.setActivationFunction(new ActivationSigmoid());
    pattern.setInputNeurons(1);
    pattern.addHiddenLayer(6);
    pattern.setOutputNeurons(1);
    return (BasicNetwork)pattern.generate();
  }

  static BasicNetwork createFeedforwardNetwork() {
    // construct a feedforward type network
    FeedForwardPattern pattern = new FeedForwardPattern();
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    // we are really just making sure no array out of bounds errors occur
    ElmanPattern elmanPattern = new ElmanPattern();
    elmanPattern.setInputNeurons(input);
    elmanPattern.addHiddenLayer(hidden);
    elmanPattern.setOutputNeurons(ideal);
    BasicNetwork network = (BasicNetwork)elmanPattern.generate();
    MLDataSet training = RandomTrainingFactory.generate(1000, 5, network.getInputCount(), network.getOutputCount(), -1, 1);
    ResilientPropagation prop = new ResilientPropagation(network,training);
    prop.iteration();
    prop.iteration();   
  }
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      ElmanPattern elman = new ElmanPattern();
      elman.setInputNeurons(dialog.getInputCount().getValue());
      elman.addHiddenLayer(dialog.getHiddenCount().getValue());
      elman.setOutputNeurons(dialog.getOutputCount().getValue());
      elman.setActivationFunction(new ActivationTANH());
      return elman.generate();
    } else
      return null;

  }
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    // we are really just making sure no array out of bounds errors occur
    ElmanPattern elmanPattern = new ElmanPattern();
    elmanPattern.setInputNeurons(input);
    elmanPattern.addHiddenLayer(hidden);
    elmanPattern.setOutputNeurons(ideal);
    BasicNetwork network = (BasicNetwork)elmanPattern.generate();
    MLDataSet training = RandomTrainingFactory.generate(1000, 5, network.getInputCount(), network.getOutputCount(), -1, 1);
    ResilientPropagation prop = new ResilientPropagation(network,training);
    prop.iteration();
    prop.iteration();   
  }
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