public void TestIncreaseNeuronCountHidden()
{
BasicNetwork network = XOR.CreateTrainedXOR();
Assert.IsTrue(XOR.VerifyXOR(network, 0.10));
PruneSelective prune = new PruneSelective(network);
prune.ChangeNeuronCount(1, 5);
BasicNetwork model = EncogUtility.SimpleFeedForward(2, 5, 0, 1, false);
CheckWithModel(model.Structure.Flat, network.Structure.Flat);
Assert.IsTrue(XOR.VerifyXOR(network, 0.10));
}
public void TestPersistEG()
{
IMLDataSet trainingSet = XOR.CreateXORDataSet();
RBFNetwork network = new RBFNetwork(2, 4, 1, RBFEnum.Gaussian);
SVDTraining training = new SVDTraining(network, trainingSet);
training.Iteration();
XOR.VerifyXOR(network, 0.1);
EncogDirectoryPersistence.SaveObject(EG_FILENAME, network);
RBFNetwork network2 = (RBFNetwork)EncogDirectoryPersistence.LoadObject(EG_FILENAME);
XOR.VerifyXOR(network2, 0.1);
}
public BasicPNN create()
{
PNNOutputMode mode = PNNOutputMode.Regression;
BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 1);
BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XORInput,
XOR.XORIdeal);
TrainBasicPNN train = new TrainBasicPNN(network, trainingSet);
train.Iteration();
XOR.VerifyXOR(network, 0.001);
return(network);
}
public void Validate(BasicNetwork network)
{
network.ClearContext();
XOR.VerifyXOR(network, 0.1);
}
public void Validate(FreeformNetwork network)
{
network.ClearContext();
XOR.VerifyXOR(network, 0.1);
}