public void TestAndGate() { NetworkModel model = new NetworkModel(); model.Layers.Add(new NeuralLayer(2, "INPUT")); model.Layers.Add(new NeuralLayer(2, "HIDDEN")); model.Layers.Add(new NeuralLayer(1, "OUTPUT")); model.Build(); NeuralData X = new NeuralData(4); X.Add(0, 0); X.Add(0, 1); X.Add(1, 0); X.Add(1, 1); NeuralData Y = new NeuralData(4); Y.Add(0); Y.Add(0); Y.Add(0); Y.Add(1); // model.Train(X, Y, iterations: 10, learningRate: 0.1); }
static void Main(string[] args) { Network model = new Network(); model.Layers.Add(new Layer(2, 0.1, "INPUT")); model.Layers.Add(new Layer(1, 0.1, "OUTPUT")); model.Build(); Console.WriteLine("----Before Training------------"); model.Print(); Console.WriteLine(); NeuralData X = new NeuralData(4); X.Add(0, 0); X.Add(0, 1); X.Add(1, 0); X.Add(1, 1); NeuralData Y = new NeuralData(4); Y.Add(0); Y.Add(0); Y.Add(0); Y.Add(1); model.Train(X, Y, iterations: 10, learningRate: 0.1); Console.WriteLine(); Console.WriteLine("----After Training------------"); model.Print(); }