public static void Main(String[] args)
{
ArrayNeuralNetwork network = new ArrayNeuralNetwork(3, 6, 3);
trainSet = countSet;
Console.WriteLine("Press enter to start training...");
Console.ReadLine();
Console.WriteLine("Starting the training.");
for (int x = 0; x < 100; x++)
{
logSquaredError(network, trainSet, x);
for (int y = 0; y < 10000; y++)
{
for (int z = 0; z < trainSet.Length; z++)
{
network.train(trainSet[z][0], trainSet[z][1]);
}
}
}
Console.WriteLine("Stopped the Training.");
for (int i = 0; i < trainSet.Length; i++)
{
Console.WriteLine(String.Format("Test number {0}: {1}", i, doubleArrayToString(network.process(trainSet[i][0]))));
}
Console.WriteLine("Press enter to start time testing of pass forward.");
Console.ReadLine();
for (int i = 0; i < 1000; i++)
{
for (int j = 0; j < 1000; j++)
{
network.process(trainSet[0][0]);
}
}
Console.WriteLine("Finished Testing the pass forward");
Console.ReadLine();
}
public static void logSquaredError(ArrayNeuralNetwork network, double[][][] testSet, int reportId)
{
Console.WriteLine("Performance Report ---------- " + reportId);
double error = 0;
for (int i = 0; i < testSet.Length; i++)
{
double[] results = network.process(testSet[i][0]);
bool success = true;
for (int j = 0; j < results.Length; j++)
{
if (Math.Abs(results[j] - testSet[i][1][j]) > 0.5)
{
success = false;
}
error += Math.Pow(results[j] - testSet[i][1][j], 2);
}
Console.WriteLine(String.Format("--- Test number {0} resulted in {1}", i, success));
}
Console.WriteLine(String.Format("The combined squared error is {0}.", error));
}