public void TestMlpBuild()
{
mlpNetwork.Instantiate();
Assert.AreEqual(mlpNetwork.CurrentError, 0);
Assert.AreEqual(mlpNetwork.HiddenLayers, 1);
Assert.AreEqual(mlpNetwork.TransferFunction, ActivationNeuroMode.SIGMOIDAL);
Assert.AreEqual(mlpNetwork.OutputSize, 1);
Assert.AreEqual(mlpNetwork.InputSize, 2);
}
public void Build(AnnBuild AnnBuilding)
{
if (network != null)
{
network.Destroy();
}
network = new Mlp(
AnnBuilding.InputUnits,
AnnBuilding.HiddenUnits,
AnnBuilding.HiddenLayers,
AnnBuilding.OutputUnits,
AnnBuilding.Bias,
AnnBuilding.ActivationNeuroMode
);
synInitMode = AnnBuilding.SynInitMode;
network.Instantiate();
status = NetworkStatus.UNTRAINED;
logger.InfoFormat("Building neural network classifier: {0}", this.ToString());
}
private void Build(uint input, uint hiddenLayers, uint[] hiddenNeurons, uint output)
{
// Build network model
mlpNetwork = new Mlp(input, hiddenNeurons, hiddenLayers, output);
mlpNetwork.Instantiate();
}