static void Main(string[] args)
{
NeuralNetwork nn = new NeuralNetwork();
nn.AddLayer(2, new Sigmoid());
nn.AddLayer(3, new Sigmoid());
nn.AddLayer(3, new Sigmoid());
nn.AddLayer(1, new Sigmoid());
nn.Build();
double[][] input = new double[][] {
new double[] { 0, 0 },
new double[] { 0, 1 },
new double[] { 1, 0 },
new double[] { 1, 1 }
};
double[][] and = new double[][] {
new double[] { 0 },
new double[] { 0 },
new double[] { 0 },
new double[] { 1 },
};
double[][] or = new double[][] {
new double[] { 0 },
new double[] { 1 },
new double[] { 1 },
new double[] { 1 },
};
double[][] xor = new double[][] {
new double[] { 0 },
new double[] { 1 },
new double[] { 1 },
new double[] { 0 },
};
nn.Train(input, xor, 10000, 0.25);
nn.Predict(input[0]);
nn.Predict(input[1]);
nn.Predict(input[2]);
nn.Predict(input[3]);
Console.ReadLine();
}
static void Main(string[] args)
{
//double[,] training_inputs = { { 0, 0, 1}, { 1, 1, 1}, { 1, 0, 1}, { 0, 1, 1}, { 0, 0, 0}, { 1, 0, 0} };
double[,] training_inputs = { { 0, 0, 1 }, { 1, 1, 1 }, { 1, 0, 1 }, { 0, 1, 1 } };
//double[] training_outputs = { 0, 1, 1, 0, 0, 1};
double[] training_outputs = { 0, 1, 1, 0 };
NeuralNetwork neuralNetwork = new NeuralNetwork();
Console.WriteLine("Synaptic-Weights before training: ");
foreach (var item in neuralNetwork.synaptic_weights)
{
Console.Write(item.ToString());
Console.Write(" , ");
}
neuralNetwork.Train(training_inputs, training_outputs, 100000);
Console.WriteLine("");
Console.WriteLine("Synaptic-Weights after training: ");
foreach (var item in neuralNetwork.synaptic_weights)
{
Console.Write(item.ToString());
Console.Write(" , ");
}
Console.WriteLine("");
Console.WriteLine("New Situation: ");
Console.Write("Input1 = ");
int a = int.Parse(Console.ReadLine());
Console.Write("Input2 = ");
int b = int.Parse(Console.ReadLine());
Console.Write("Input3 = ");
int c = int.Parse(Console.ReadLine());
Console.WriteLine("");
Console.WriteLine("New Situation data: {0}, {1}, {2} ", a, b, c);
Console.WriteLine("");
double[,] newInputs = { { a, b, c } };
double[] outputs = neuralNetwork.Think(newInputs);
int roundOutput = (int)Math.Round(outputs[0]);
double roundPercent = 0;
if (roundOutput == 1)
{
double percent = outputs[0] * 100;
roundPercent = Math.Round(percent, 2);
}
else
{
double percent = (1 - outputs[0]) * 100;
roundPercent = Math.Round(percent, 2);
}
Console.Write("With a probability of " + roundPercent + "% the Output is: ");
Console.Write(Math.Round(outputs[0]));
Console.Write(" (");
Console.Write(outputs[0]);
Console.Write(")");
Console.ReadKey();
}
