static void Main()
{
const uint num_input = 3;
const uint num_output = 1;
const uint num_layers = 4;
const uint num_neurons_hidden = 5;
const float desired_error = 0.0001F;
const uint max_epochs = 5000;
const uint epochs_between_reports = 1000;
using(NeuralNet net = new NeuralNet(NetworkType.LAYER, num_layers, num_input, num_neurons_hidden, num_neurons_hidden, num_output))
{
net.ActivationFunctionHidden = ActivationFunction.SIGMOID_SYMMETRIC;
net.ActivationFunctionOutput = ActivationFunction.LINEAR;
net.TrainingAlgorithm = TrainingAlgorithm.TRAIN_RPROP;
using (TrainingData data = new TrainingData("..\\..\\..\\datasets\\scaling.data"))
{
net.SetScalingParams(data, -1, 1, -1, 1);
net.ScaleTrain(data);
net.TrainOnData(data, max_epochs, epochs_between_reports, desired_error);
net.Save("..\\..\\..\\datasets\\scaling.net");
Console.ReadKey();
}
}
}
