public void Execute(IExampleInterface app)
{
this.app = app;
var temp = new TemporalXOR();
IMLDataSet trainingSet = temp.Generate(100);
var jordanNetwork = (BasicNetwork)CreateJordanNetwork();
var feedforwardNetwork = (BasicNetwork)CreateFeedforwardNetwork();
double elmanError = TrainNetwork("Jordan", jordanNetwork, trainingSet);
double feedforwardError = TrainNetwork("Feedforward", feedforwardNetwork, trainingSet);
app.WriteLine("Best error rate with Jordan Network: " + elmanError);
app.WriteLine("Best error rate with Feedforward Network: " + feedforwardError);
app.WriteLine("Jordan will perform only marginally better than feedforward.\nThe more output neurons, the better performance a Jordan will give.");
}
public void Execute(IExampleInterface app)
{
TemporalXOR temp = new TemporalXOR();
IMLDataSet trainingSet = temp.Generate(120);
FreeformNetwork elmanNetwork = FreeformNetwork.CreateElman(1, 6, 1, new ActivationSigmoid());
FreeformNetwork feedforwardNetwork = FreeformNetwork.CreateFeedforward(1, 6, 0, 1, new ActivationSigmoid());
double feedforwardError = TrainNetwork("feedforward", feedforwardNetwork, trainingSet);
double elmanError = TrainNetwork("elman", elmanNetwork, trainingSet);
Console.WriteLine(@"Best error rate with Elman Network: " + elmanError);
Console.WriteLine(@"Best error rate with Feedforward Network: "
+ feedforwardError);
Console.WriteLine(@"Elman should be able to get into the 10% range,\nfeedforward should not go below 25%.\nThe recurrent Elment net can learn better in this case.");
Console.WriteLine(@"If your results are not as good, try rerunning, or perhaps training longer.");
EncogFramework.Instance.Shutdown();
}
public void Execute(IExampleInterface app)
{
this.app = app;
var temp = new TemporalXOR();
IMLDataSet trainingSet = temp.Generate(100);
if (app.Args.Length > 0)
{
trainingSet = temp.Generate(Convert.ToInt16(app.Args[0]));
}
var elmanNetwork = (BasicNetwork)CreateElmanNetwork(trainingSet.InputSize);
var feedforwardNetwork = (BasicNetwork)CreateFeedforwardNetwork(trainingSet.InputSize);
double elmanError = TrainNetwork("Elman", elmanNetwork, trainingSet, "Leven");
double feedforwardError = TrainNetwork("Feedforward", feedforwardNetwork, trainingSet, "Leven");
app.WriteLine("Best error rate with Elman Network: " + elmanError);
app.WriteLine("Best error rate with Feedforward Network: " + feedforwardError);
app.WriteLine("(Elman should outperform feed forward)");
app.WriteLine("If your results are not as good, try rerunning, or perhaps training longer.");
}
