public static void Run()
{
Random rng = new Random();
DataSet data = new XorDataSetGenerator();
int inputDimension = 2;
int hiddenDimension = 3;
int outputDimension = 1;
int hiddenLayers = 1;
double learningRate = 0.001;
double initParamsStdDev = 0.08;
INetwork nn = NetworkBuilder.MakeFeedForward(inputDimension,
hiddenDimension,
hiddenLayers,
outputDimension,
data.GetModelOutputUnitToUse(),
data.GetModelOutputUnitToUse(),
initParamsStdDev, rng);
int reportEveryNthEpoch = 10;
int trainingEpochs = 100000;
Trainer.train <NeuralNetwork>(trainingEpochs, learningRate, nn, data, reportEveryNthEpoch, rng);
Console.WriteLine("Training Completed.");
Console.WriteLine("Test: 1,1");
Matrix input = new Matrix(new double[] { 1, 1 });
Graph g = new Graph(false);
Matrix output = nn.Activate(input, g);
Console.WriteLine("Test: 1,1. Output:" + output.W[0]);
Matrix input1 = new Matrix(new double[] { 0, 1 });
Graph g1 = new Graph(false);
Matrix output1 = nn.Activate(input1, g1);
Console.WriteLine("Test: 0,1. Output:" + output1.W[0]);
Console.WriteLine("done.");
}