static void Main(string[] args)
{
LearningRateExperiment _experiment = new LearningRateExperiment();
// Load config XML.
XmlDocument xmlConfig = new XmlDocument();
xmlConfig.Load(NEURAL_CONFIG_FILE);
_experiment.Initialize("blah", xmlConfig.DocumentElement);
LearningRateExperiment.CreateNetwork("temp", 2, 3, 1);
var genome = _experiment.LoadPopulation(XmlReader.Create("temp"))[0];
var decoder = _experiment.CreateGenomeDecoder();
Console.WriteLine("Original Network");
Backprop(genome, decoder, 0);
Console.WriteLine("Backpropped Learning Rate = 1");
Backprop(genome, decoder, 1);
int epochs = 1000000;
double learningRate = 0.1;
Console.WriteLine("Backpropped Learning Rate = {0}, {1} epochs", learningRate, epochs);
BackpropEpochs(genome, decoder, 0.01, 100000);
}
static void Main(string[] args)
{
LearningRateExperiment _experiment = new LearningRateExperiment();
// Load config XML.
XmlDocument xmlConfig = new XmlDocument();
xmlConfig.Load(NEURAL_CONFIG_FILE);
_experiment.Initialize("blah", xmlConfig.DocumentElement);
LearningRateExperiment.CreateNetwork("temp", 2, 3, 1);
var genome = _experiment.LoadPopulation(XmlReader.Create("temp"))[0];
var decoder = _experiment.CreateGenomeDecoder();
Console.WriteLine("Original Network");
Backprop(genome, decoder, 0);
Console.WriteLine("Backpropped Learning Rate = 1");
Backprop(genome, decoder, 1);
int epochs = 1000000;
double learningRate = 0.1;
Console.WriteLine("Backpropped Learning Rate = {0}, {1} epochs", learningRate, epochs);
BackpropEpochs(genome, decoder, 0.01, 100000);
}
