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();
}