public OutputLayer(Activation activation, TrainingInfo trainInfo, int size) { var neurons = new OutputNeuron[size]; for (int i = 0; i < size; i++) neurons[i] = new OutputNeuron(activation, trainInfo); this.neurons = neurons; }
public HiddenLayer(Activation activation, TrainingInfo trainInfo, int size) { var neurons = new Neuron[size + 1]; for (int i = 0; i < size; i++) neurons[i] = new HiddenNeuron(activation, trainInfo); neurons[size] = new BiasNeuron(); this.neurons = neurons; }
public OutputLayer(Activation activation, TrainingInfo trainInfo, int size) { var neurons = new OutputNeuron[size]; for (int i = 0; i < size; i++) { neurons[i] = new OutputNeuron(activation, trainInfo); } this.neurons = neurons; }
public HiddenLayer(Activation activation, TrainingInfo trainInfo, int size) { var neurons = new Neuron[size + 1]; for (int i = 0; i < size; i++) { neurons[i] = new HiddenNeuron(activation, trainInfo); } neurons[size] = new BiasNeuron(); this.neurons = neurons; }
public Network(Activation activation, TrainingInfo trainInfo, int inputSize, int[] hiddenSizes, int outputSize) { this.InputSize = inputSize; this.HiddenSizes = hiddenSizes; this.OutputSize = outputSize; this.activation = activation; this.inputLayer = new InputLayer(inputSize); this.hiddenLayers = hiddenSizes .Select(size => new HiddenLayer(activation, trainInfo, size)) .ToArray(); this.outputLayer = new OutputLayer(activation, trainInfo, outputSize); ConnectLayers(); }
public Neuron(Activation activation, TrainingInfo trainInfo) { this.activation = activation; this.trainInfo = trainInfo; }
public HiddenNeuron(Activation activation, TrainingInfo trainInfo) : base(activation, trainInfo) { }
public OutputNeuron(Activation activation, TrainingInfo trainInfo) : base(activation, trainInfo) { }