private void buttonLoadNetwork_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.Filter = "All Files (*.*)|*.*";
openFileDialog.FilterIndex = 1;
openFileDialog.Multiselect = false;
if (openFileDialog.ShowDialog() == DialogResult.OK)
{
mlpNetwork = new MLPNetwork();
try
{
mlpNetwork.LoadNetwork(openFileDialog.FileName);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
mlpNetwork = null;
}
}
}
private void buttonTrain_Click(object sender, EventArgs e)
{
if (numericUpDownLayersCount.Value == 0 || numericUpDownNeuronsCount.Value == 0 || numericUpDownIterationsCount.Value == 0 || comboBoxActivationFunction.Text == string.Empty || comboBoxProblemType.Text == string.Empty)
{
MessageBox.Show("Brak zdefiniowanych wartości pól lub niedozwolone wartości pól.", "Błąd", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
if(inputDataFileName == string.Empty)
{
MessageBox.Show("Brak danych treningowych.", "Błąd", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
int layersCount = Decimal.ToInt32(numericUpDownLayersCount.Value);
int neuronsCount = Decimal.ToInt32(numericUpDownNeuronsCount.Value);
int iterationsCount = Decimal.ToInt32(numericUpDownIterationsCount.Value);
double learningRate = Decimal.ToDouble(numericUpDownLearningRate.Value);
double momentum = Decimal.ToDouble(numericUpDownMomentum.Value);
mlpNetwork = new MLPNetwork(layersCount, neuronsCount, checkBoxBias.Checked,comboBoxActivationFunction.Text == "bipolarna" ? ActivationFunctionType.Bipolar : ActivationFunctionType.Unipolar, comboBoxProblemType.Text == "klasyfikacja" ? ProblemType.Classification : ProblemType.Regression, inputDataFileName );
double[][] errors = mlpNetwork.Train(iterationsCount, learningRate, momentum);
chartErrors.Series["Błędy test."].Points.Clear();
chartErrors.Series["Błędy walid."].Points.Clear();
for (int i = 0; i < errors[0].Length; i++)
{
chartErrors.Series["Błędy test."].Points.AddXY(i + 1, errors[0][i]);
chartErrors.Series["Błędy walid."].Points.AddXY(i + 1, errors[1][i]);
}
mlpNetwork.SaveNetwork("network");
}
