/// <summary> /// Build a new BackPropagation learning algorithm instance /// with alpha = 0,5 and gamma = 0,3 /// </summary> /// <param name="nn">The neural network to train</param> public BackPropagationLearningAlgorithm(NeuralNetwork nn) : base(nn) { }
/// <summary> /// Build a new Genetic NeuralNetwork from the Neural Network given as parameter /// </summary> /// <param name="n">The neural network model</param> public GeneticNeuralNetwork(NeuralNetwork n) { nn = n; int size = 0; for (int i = 0; i < nn.N_Layers; i++) size += (nn[i].N_Inputs + 1) * nn[i].N_Neurons; genes = new float[size]; }
/// <summary> /// Learning algorithm constructor /// </summary> /// <param name="n">The neural network to train</param> public LearningAlgorithm(NeuralNetwork n) { nn = n; }
/// <summary> /// GeneticLearningAlgorithm constructor /// </summary> /// <param name="nn">The neural network to train</param> public GeneticLearningAlgorithm(NeuralNetwork nn) : base(nn) { population = new ArrayList(); for (int i = 0; i < POPULATION_SIZE; i++) population.Add(Muted_NeuralNetwork); }