public void TestDynamicXOR()
{
Func <int, int, double> inputFunc = OnInputFunc;
Func <int, int, double> idealFunc = delegate(int chunk, int index) { return(XOR.XORIdeal[chunk][index]); };
var input = new FuncMLDataProvider(inputFunc, XOR.XORInput.Length, XOR.XORInput[0].Length);
var ideal = new FuncMLDataProvider(idealFunc, XOR.XORIdeal.Length, XOR.XORIdeal[0].Length);
var ds = new DynamicMLDataSet(input, ideal);
var network = new BasicNetwork();
network.AddLayer(new BasicLayer(new ActivationSigmoid(), false, ds.InputSize));
network.AddLayer(new BasicLayer(new ActivationSigmoid(), false, ds.InputSize + 1));
network.AddLayer(new BasicLayer(new ActivationSigmoid(), false, ds.IdealSize));
network.Structure.FinalizeStructure();
network.Reset(42);
var trainer = new Encog.Neural.Networks.Training.Propagation.Resilient.ResilientPropagation(network, ds);
int maxIteration = 300;
int iteration = 0;
do
{
trainer.Iteration();
Debug.WriteLine(++iteration + ": Error = " + trainer.Error);
} while(trainer.Error > 0.0001 && maxIteration > iteration);
Assert.IsTrue(iteration < maxIteration);
}
public void TestDynamicXOR()
{
Func<int, int, double> inputFunc = OnInputFunc;
Func<int, int, double> idealFunc = delegate(int chunk, int index) { return XOR.XORIdeal[chunk][index]; };
var input = new FuncMLDataProvider(inputFunc, XOR.XORInput.Length, XOR.XORInput[0].Length);
var ideal = new FuncMLDataProvider(idealFunc, XOR.XORIdeal.Length, XOR.XORIdeal[0].Length);
var ds = new DynamicMLDataSet(input, ideal);
var network = new BasicNetwork();
network.AddLayer(new BasicLayer(new ActivationSigmoid(), false, ds.InputSize));
network.AddLayer(new BasicLayer(new ActivationSigmoid(), false, ds.InputSize + 5));
network.AddLayer(new BasicLayer(new ActivationSigmoid(), false, ds.IdealSize));
network.Structure.FinalizeStructure();
network.Reset(42);
var trainer = new Encog.Neural.Networks.Training.Propagation.Resilient.ResilientPropagation(network, ds);
int maxIteration = 300;
int iteration = 0;
do
{
trainer.Iteration();
Debug.WriteLine(++iteration + ": Error = " + trainer.Error);
} while(trainer.Error > 0.0001 && maxIteration > iteration);
Assert.IsTrue(iteration < maxIteration);
}
