//TODO
private void btnTrain_Click(object sender, EventArgs e)
{
if (trainingData == null)
{
MessageBox.Show("No TrainingData loaded!");
return;
}
// Check if NN is null. "first use"
if (NN == null)
{
NN = new NeuralNetwork(3, (int)numericHidden.Value, 1, (double)numericLearnrate.Value, (double)numericMomentum.Value);
NN.FireMaxAccuracyReached += NN_RecieveMaxAccuracyReached;
NN.FireMaxIterationsReached += NN_RecieveMaxIterationsReached;
NN.FirePerformanceInfo += NN_RecievePerformanceInfo;
NN.FireTrainingComplete += NN_RecieveTrainingComplete;
NN.FireOutputComparison += NN_RecieveOutputComparison;
NN.FireTestingComplete += NN_RecieveTestingComplete;
NN.FireTestingResultInfo += NN_RecieveTestingResultInfo;
}
// Alerts configuration change
if (numericHidden.Value != NN.NumberOfHidden)
{
if (MessageBox.Show("Do you want to reset neural-network with new cofiguration?", "Configuration of hidden node has changed!", MessageBoxButtons.YesNo) == DialogResult.Yes)
{
NN = new NeuralNetwork(3, (int)numericHidden.Value, 1, (double)numericLearnrate.Value, (double)numericMomentum.Value); // TODO: (FIX)Slightly hardcoded for assignment
NN.FireMaxAccuracyReached += NN_RecieveMaxAccuracyReached;
NN.FireMaxIterationsReached += NN_RecieveMaxIterationsReached;
NN.FirePerformanceInfo += NN_RecievePerformanceInfo;
NN.FireTrainingComplete += NN_RecieveTrainingComplete;
NN.FireOutputComparison += NN_RecieveOutputComparison;
NN.FireTestingComplete += NN_RecieveTestingComplete;
NN.FireTestingResultInfo += NN_RecieveTestingResultInfo;
}
else
{
numericHidden.Value = NN.NumberOfHidden;
return;
}
}
Action action = () =>
{
NN.LearningRate = (double)numericLearnrate.Value;
NN.Momentum = (double)numericMomentum.Value;
NN.Train(trainingData, (int)numericIterations.Value, (double)(numericPercentage.Value/100), 10, (int)numericAccuracyFilter.Value);
//MessageBox.Show("Traning Done!","Traning ");
};
SetupPerformanceChart(true);
btnTrain.Enabled = false;
btnTest.Enabled = false;
btnReset.Enabled = false;
btnStop.Enabled = true;
Thread TrainingAction = new Thread(() => action());
TrainingAction.Start();
}
private void btReset_Click(object sender, EventArgs e)
{
if (NN != null)
{
NN = new NeuralNetwork(3, (int)numericHidden.Value, 1, (double)numericLearnrate.Value, (double)numericMomentum.Value);
NN.FireMaxAccuracyReached += NN_RecieveMaxAccuracyReached;
NN.FireMaxIterationsReached += NN_RecieveMaxIterationsReached;
NN.FirePerformanceInfo += NN_RecievePerformanceInfo;
NN.FireTrainingComplete += NN_RecieveTrainingComplete;
NN.FireOutputComparison += NN_RecieveOutputComparison;
NN.FireTestingComplete += NN_RecieveTestingComplete;
NN.FireTestingResultInfo += NN_RecieveTestingResultInfo;
}
}
private void loadNeuralNetworkToolStripMenuItem_Click(object sender, EventArgs e)
{
if (NN != null)
{
if (MessageBox.Show("Do you want to overwrite it?", "Neural-Network allready exist!", MessageBoxButtons.YesNo) == DialogResult.No)
{
return;
}
}
// open dialog
OpenFileDialog dialog = new OpenFileDialog();
dialog.Filter = "Txt files|*.txt|XML files|*.xml";
if (dialog.ShowDialog() == DialogResult.OK)
{
if (NN != null)
{
NN.LoadNN(dialog.FileName);
}
else
{
NN = new NeuralNetwork(3, (int)numericHidden.Value, 1, (double)numericLearnrate.Value, (double)numericMomentum.Value);
NN.FireMaxAccuracyReached += NN_RecieveMaxAccuracyReached;
NN.FireMaxIterationsReached += NN_RecieveMaxIterationsReached;
NN.FirePerformanceInfo += NN_RecievePerformanceInfo;
NN.FireTrainingComplete += NN_RecieveTrainingComplete;
NN.FireOutputComparison += NN_RecieveOutputComparison;
NN.FireTestingComplete += NN_RecieveTestingComplete;
NN.FireTestingResultInfo += NN_RecieveTestingResultInfo;
NN.LoadNN(dialog.FileName);
numericHidden.Value = NN.NumberOfHidden;
numericLearnrate.Value = (decimal)NN.LearningRate;
numericMomentum.Value = (decimal)NN.Momentum;
}
}
}
