private void worker_RunWorkerCompleted(object sender, RunWorkerCompletedEventArgs e)
{
var worker = (BackgroundWorker)sender;
worker.DoWork -= worker_DoWork;
worker.ProgressChanged -= _progressChangedEventHandler;
worker.RunWorkerCompleted -= worker_RunWorkerCompleted;
var parameter = (WorkerResultInfo)e.Result;
if (parameter.TestingSubsetIndex.HasValue && parameter.NoOfSubsets.HasValue)
{
OnCompleteCallback?.Invoke();
Succesor?.Start();
}
}
private void worker_RunWorkerCompleted(object sender, RunWorkerCompletedEventArgs e)
{
var worker = (BackgroundWorker)sender;
worker.DoWork -= worker_DoWork;
worker.ProgressChanged -= _progressChangedEventHandler;
worker.RunWorkerCompleted -= worker_RunWorkerCompleted;
var parameter = (WorkerResultInfo)e.Result;
var network = parameter.Network;
var savePath = _trainingModel.NeuralNetworkPath;
var nnModel = new NnModel
{
Path = savePath,
InputNodes = string.Join(";", _trainingModel.TrainingData.InputVariables),
OutputNodes = string.Join(";", _trainingModel.TrainingData.OutputVariables)
};
if (File.Exists(savePath))
{
File.Delete(savePath);
_nnRepository.Update(nnModel);
}
else
{
_nnRepository.Add(nnModel);
}
network.Save(savePath);
if (parameter.TestingSubsetIndex.HasValue && parameter.NoOfSubsets.HasValue)
{
OnCompleteCallback?.Invoke();
Succesor?.Start(parameter.NoOfSubsets, parameter.TestingSubsetIndex);
}
}