/// <summary>
/// Program entry point.
/// </summary>
/// <param name="app">Holds arguments and other info.</param>
public void Execute(IExampleInterface app)
{
BasicNetwork network = CreateNetwork();
IMLTrain train;
if (app.Args.Length > 0 && String.Compare(app.Args[0], "anneal", true) == 0)
{
train = new NeuralSimulatedAnnealing(
network, new PilotScore(), 10, 2, 100);
}
else
{
train = new NeuralGeneticAlgorithm(
network, new NguyenWidrowRandomizer(),
new PilotScore(), 500, 0.1, 0.25);
}
int epoch = 1;
for (int i = 0; i < 50; i++)
{
train.Iteration();
Console.WriteLine(@"Epoch #" + epoch + @" Score:" + train.Error);
epoch++;
}
Console.WriteLine(@"\nHow the winning network landed:");
network = (BasicNetwork)train.Method;
var pilot = new NeuralPilot(network, true);
Console.WriteLine(pilot.ScorePilot());
EncogFramework.Instance.Shutdown();
}
/// <summary>
/// Program entry point.
/// </summary>
/// <param name="app">Holds arguments and other info.</param>
public void Execute(IExampleInterface app)
{
BasicNetwork network = CreateNetwork();
IMLTrain train;
if (app.Args.Length > 0 && String.Compare(app.Args[0], "anneal", true) == 0)
{
train = new NeuralSimulatedAnnealing(
network, new PilotScore(), 10, 2, 100);
}
else
{
train = new NeuralGeneticAlgorithm(
network, new FanInRandomizer(),
new PilotScore(), 500, 0.1, 0.25);
}
int epoch = 1;
for (int i = 0; i < 50; i++)
{
train.Iteration();
Console.WriteLine(@"Epoch #" + epoch + @" Score:" + train.Error);
epoch++;
}
Console.WriteLine(@"\nHow the winning network landed:");
network = (BasicNetwork) train.Method;
var pilot = new NeuralPilot(network, true);
Console.WriteLine(pilot.ScorePilot());
EncogFramework.Instance.Shutdown();
}
public double CalculateScore(IMLMethod network)
{
NeuralPilot pilot = new NeuralPilot((BasicNetwork)network, false);
return pilot.ScorePilot();
}
public double CalculateScore(IMLMethod network)
{
NeuralPilot pilot = new NeuralPilot((BasicNetwork)network, false);
return(pilot.ScorePilot());
}