Documentation of 'org.encog.neural.pattern.SOMPattern' Java class
SOMPattern
org.encog.neural.pattern

Class SOMPattern

  • All Implemented Interfaces:
    NeuralNetworkPattern


    public class SOMPattern
    extends java.lang.Object
    implements NeuralNetworkPattern
    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.
    • Constructor Detail

      • SOMPattern

        public SOMPattern()
    • Method Detail

      • addHiddenLayer

        public void addHiddenLayer(int count)
        Add a hidden layer. SOM networks do not have hidden layers, so this will throw an error.
        Specified by:
        addHiddenLayer in interface NeuralNetworkPattern
        Parameters:
        count - The number of hidden neurons.
      • setActivationFunction

        public void setActivationFunction(ActivationFunction activation)
        Set the activation function. A SOM uses a linear activation function, so this method throws an error.
        Specified by:
        setActivationFunction in interface NeuralNetworkPattern
        Parameters:
        activation - The activation function to use.
      • setInputNeurons

        public void setInputNeurons(int count)
        Set the input neuron count.
        Specified by:
        setInputNeurons in interface NeuralNetworkPattern
        Parameters:
        count - The number of neurons.
      • setOutputNeurons

        public void setOutputNeurons(int count)
        Set the output neuron count.
        Specified by:
        setOutputNeurons in interface NeuralNetworkPattern
        Parameters:
        count - The number of neurons.

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