Examples of org.encog.neural.pattern.SOMPattern

org.encog.neural.pattern.SOMPattern
A self organizing map is a neural network pattern with an input and output layer. There is no hidden layer. The winning neuron, which is that neuron with the higest output is the winner, this winning neuron is often used to classify the input into a group. @author jheaton


  private static MLMethod createSOM() {
    CreateSOMDialog dialog = new CreateSOMDialog(EncogWorkBench
        .getInstance().getMainWindow());
    if (dialog.process()) {
      SOMPattern som = new SOMPattern();
      som.setInputNeurons(dialog.getInputCount().getValue());
      som.setOutputNeurons(dialog.getOutputCount().getValue());
      return som.generate();
    } else
      return null;
  }

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        layers.get(1), output);


    final int inputCount = inputLayer.getCount();
    final int outputCount = outputLayer.getCount();


    final SOMPattern pattern = new SOMPattern();
    pattern.setInputNeurons(inputCount);
    pattern.setOutputNeurons(outputCount);
    return pattern.generate();
  }

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        layers.get(1), output);


    final int inputCount = inputLayer.getCount();
    final int outputCount = outputLayer.getCount();


    final SOMPattern pattern = new SOMPattern();
    pattern.setInputNeurons(inputCount);
    pattern.setOutputNeurons(outputCount);
    return pattern.generate();
  }

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Related Classes of org.encog.neural.pattern.SOMPattern

org.encog.ml.factory.method.SOMFactory

org.encog.neural.som.SOM

org.encog.workbench.process.CreateNeuralNetwork

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