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Abstract : NeuralNetwork

Class description:

A new experimental class for simple feed-forward neural networks.

Methods:

  • addLayer
  • getOutput
  • getWeight
  • runWith
  • setWeight
    addLayer( self, count )

    Adds a layer to the output end of the neural network, with count neurons. The first layer added serves as the input layer, and then subsequent layers serve as hidden or output layers.

    To create a network with one hidden layer, for example, you would first call add-layer for the input layer, then the hidden layer, then the output layer.

    getOutput( self, position )

    Returns the value at index position of the output layer. This assumes that run-with has already been called to actually run the neural network.

    getWeight( self, theLayer, fn, tn )

    Sets the input to the node number tn on layer theLayer, coming from node number fn on layer number theLayer - 1 to weight. Normally you wouldn't need to use this method, since the method get-output is the preferred way to retrieve network output.

    runWith( self, inputList )

    Sets the inputs of the neural network to the values in inputList, and runs the network. Output values can then be retrieved with get-output.

    setWeight( self, theLayer, fn, tn, weight )

    Sets the input to the node number tn on layer theLayer, coming from node number fn on layer number theLayer - 1 to weight.