public static void Test()
{
NeuralNetwork neuralNetwork = new NeuralNetwork(new[] { 3, 2, 2 });
neuralNetwork.W[0] = new Matrix(3, 2, new double[] {
0.22, 0.10,
0.08, -0.16,
-0.07, 0.15
});
neuralNetwork.W[1] = new Matrix(2, 2, new double[] {
0.10, 0.20,
-0.05, 0.10
});
neuralNetwork.BackPropagation(new Vector(new[] { 5d, 10, 15 }),
new Vector(new[] { 0d, 1 }),
0.5);
}
public void Teach()
{
Errors.Clear();
DateTime t1 = DateTime.Now;
for (int epoсh = 0; epoсh < EPOCH_NUMBER; epoсh++)
{
double epohError = 0;
//System.Diagnostics.Debug.WriteLine("----" + "epoсh" + epoсh+"----");
string[] folders = Directory.GetDirectories(m_folder);
for (int i = 0; i < folders.Length; i++)
{
string[] files = Directory.GetFiles(folders[i]);
for (int j = 0; j < files.Length; j++)
{
char ch = Path.GetFileName(folders[i])[0];
double[,,] arrImage = BitmapConverter.BitmapToDoubleRgb(new Bitmap(files[j]));
Vector input = ArrayImageService.formInputVectorForNeuralNetwork(arrImage);
double err = m_network.BackPropagation(input, LettersInformator.GetVectorForLetter(ch), 0.5);
//System.Diagnostics.Debug.WriteLine(String.Format("letter: '{0}' error: {1:0.0000}", ch, err));
epohError += err;
}
}
Errors.Add(epohError);
//System.Diagnostics.Debug.WriteLine(String.Format("EPOCH: '{0}' ERROR: {1:0.0000}", epoсh, epohError));
//System.Diagnostics.Debug.WriteLine("_________________________________");
}
DateTime t2 = DateTime.Now;
System.Diagnostics.Debug.WriteLine("Время обучения: " + (t2 - t1));
}