private void ParallelTrainingRProp()
{
var neuralNetworkRProp = new MultiThreadNeuralNetworkRProp(new ActivationSigmoid {
Alpha = 1
}, NetworkStructure);
var inputSets = InputDatasets.ToArray();
var outputSets = OutputDatasets.ToArray();
double count = 0;
double iteration = 0.0;
while (iteration < TrainingConfiguration.EndIteration - TrainingConfiguration.StartIteration)
{
var error = neuralNetworkRProp.Train(inputSets, outputSets);
if (count >= 500)
{
count = 0;
Console.WriteLine($"Iteration: {iteration}\t Error: {error}");
}
count++;
iteration++;
}
neuralNetworkRProp.SaveMemory(FileManager.MemoryFolderPath + "\\memory.txt", NetworkStructure);
// Запись события об успешном обучении:
LastTrainingSuccess = true;
}
private void TrainingGeneticAlg(bool unsafeMode = false)
{
GeneticAlgorithmTeacher geneticAlgTeacher = new GeneticAlgorithmTeacher
{
NetworkStructure = NetworkStructure,
InputDatasets = InputDatasets.ToList(),
OutputDatasets = OutputDatasets.ToList()
};
geneticAlgTeacher.StartTraining(TrainingConfiguration.EndIteration - TrainingConfiguration.StartIteration,
unsafeMode,
TrainingConfiguration.MemoryFolder + "//memory.txt");
// Запись события об успешном обучении:
LastTrainingSuccess = true;
}
