static void Main()
{
const uint num_input = 2;
const uint num_output = 1;
const uint num_layers = 3;
const uint num_neurons_hidden = 3;
const float desired_error = 0.001F;
const uint max_epochs = 500000;
const uint epochs_between_reports = 1000;
using (NeuralNet net = new NeuralNet(NetworkType.LAYER, num_layers, num_input, num_neurons_hidden, num_output))
{
net.ActivationFunctionHidden = ActivationFunction.SIGMOID_SYMMETRIC;
net.ActivationFunctionOutput = ActivationFunction.SIGMOID_SYMMETRIC;
net.TrainOnFile("..\\..\\..\\examples\\xor.data", max_epochs, epochs_between_reports, desired_error);
net.Save("..\\..\\..\\examples\\xor_float.net");
Console.ReadKey();
}
}