Network randomConnections(uint inputLayerSize, uint outputLayerSize, uint hiddenLayers, uint hiddenLayerMaxSize, uint maxConnections)() if (inputLayerSize > 0 && outputLayerSize > 0 && hiddenLayerMaxSize > 0 && maxConnections > 0);
- Parameters
inputLayerSize Number of neurons in the input layer outputLayerSize Number of neurons in the output layer hiddenLayers Number of 'hidden' inner layers hiddenLayerMaxSize Maximum number of neurons in each hidden layer maxConnections Maximum number of connections for each neurons, minimum is set to 1
Generator to create neural net based genomes with a random number of connections and hidden layer neurons.
Network denseNet(uint inputLayerSize, uint outputLayerSize, uint hiddenLayers, uint hiddenLayerSize)() if (inputLayerSize > 0 && outputLayerSize > 0 && hiddenLayers > 0 && hiddenLayerSize > 0);
- Parameters
inputLayerSize Number of neurons in the input layer outputLayerSize Number of neurons in the output layer hiddenLayers Number of 'hidden' inner layers hiddenLayerSize Number of neurons in each hidden layer
Creates a neural net with the given number of layers. Every node has a connection to each node in the previous layer.