static void Main(string[] args)
{
int[] layers = { 4, 6, 4 };
SMiLe.NeuralNet net = new NeuralNet(layers);
List<List<double>> inputvs2 = new List<List<double>>();
inputvs2.Add(new List<double>() { 0, 0, 0, 0 });
inputvs2.Add(new List<double>(){ 0, 0, 0, 1 });
inputvs2.Add(new List<double>(){ 0,0,1, 0 });
inputvs2.Add(new List<double>() { 0, 0, 1, 1 });
inputvs2.Add(new List<double>() { 0, 1, 0, 0 });
inputvs2.Add(new List<double>() { 0, 1, 0, 1 });
inputvs2.Add(new List<double>() { 0, 1, 1, 1 });
inputvs2.Add(new List<double>() { 1, 0, 0, 0 });
inputvs2.Add(new List<double>() { 1, 0, 0, 1 });
//inputvs2.Add(new List<double>() { 1, 0, 1, 0 });
inputvs2.Add(new List<double>() { 1, 0, 1, 1 });
inputvs2.Add(new List<double>() { 1, 1, 0, 0 });
inputvs2.Add(new List<double>() { 1, 1, 0, 1 });
inputvs2.Add(new List<double>() { 1, 1, 1, 1 });
List<List<double>> outputvs2 = new List<List<double>>();
outputvs2.Add(new List<double>() { 0, 0, 0, 0 });
outputvs2.Add(new List<double>() { 0, 0, 0, 1 });
outputvs2.Add(new List<double>() { 0, 0, 1, 0 });
outputvs2.Add(new List<double>() { 0, 0, 1, 1 });
outputvs2.Add(new List<double>() { 0, 1, 0, 0 });
outputvs2.Add(new List<double>() { 0, 1, 0, 1 });
outputvs2.Add(new List<double>() { 0, 1, 1, 1 });
outputvs2.Add(new List<double>() { 1, 0, 0, 0 });
outputvs2.Add(new List<double>() { 1, 0, 0, 1 });
//outputvs2.Add(new List<double>() { 1, 0, 1, 0 });
outputvs2.Add(new List<double>() { 1, 0, 1, 1 });
outputvs2.Add(new List<double>() { 1, 1, 0, 0 });
outputvs2.Add(new List<double>() { 1, 1, 0, 1 });
outputvs2.Add(new List<double>() { 1, 1, 1, 1 });
List<List<double>> testing = new List<List<double>>();
List<List<double>> testout = new List<List<double>>();
testing.Add(new List<double>() {1, 0, 1, 0 });
for (int ii = 0; ii < 100; ii++)
{
net.train(inputvs2, outputvs2, 2);
System.Console.WriteLine(net.error(inputvs2, outputvs2));
}
List<double> output = net.evaluate(testing[0]);
net.SAVE("neural.net", net);
NeuralNet net2 = new NeuralNet(layers);
net2 = net2.LOAD("neural.net");
NeuralNet net34 = new NeuralNet().LOAD("neural.net");
List<double> testing2 = new List<double>() { 0, 0, 1, 0 };
output = net34.evaluate(testing2);
//System.Console.WriteLine(net.error(testing, testout));
}
/// <summary>
/// SAVES the neural net to a file
/// ex: nn.SAVE("neural.net", nn);
/// </summary>
/// <param name="filename">filename, where the neural net is saved</param>
/// <param name="nn">the neural net to save</param>
public void SAVE(string filename, NeuralNet nn)
{
Stream stream = File.Open(filename, FileMode.Create);
BinaryFormatter bFormatter = new BinaryFormatter();
bFormatter.Serialize(stream, nn);
stream.Close();
}
