public void SetUp()
{
_testInput1 = new Connection (1, 0.1);
_testInput2 = new Connection (2, 0.2);
_testInputs = new List<Connection> { _testInput1, _testInput2 };
_testOutput = new Connection (0, 1.0);
_testOutputs = new List<Connection> { _testOutput };
_sigmoidAlpha = TunableParameterService.Instance.SigmoidAlpha;
_testNeuron = new MlpNeuron (_testInputs, _testOutputs, FunctionType.Sigmoid);
}
IEnumerable<Neuron> CreateInputLayer()
{
var inputLayer = new List<Neuron>();
foreach (var input in Inputs)
{
var newNeuron = new MlpNeuron(new List<Connection> { input }, new List<Connection>(), FunctionType.Linear);
inputLayer.Add(newNeuron);
Neurons.Add(newNeuron);
}
return inputLayer;
}
IEnumerable<Neuron> CreateOutputLayer()
{
var outputLayer = new List<Neuron>();
foreach (var output in Outputs)
{
var outputNode = new MlpNeuron(new List<Connection>(), new List<Connection> { output }, FunctionType.Linear);
outputLayer.Add(outputNode);
Neurons.Add(outputNode);
}
return outputLayer;
}
/// <summary>
/// Creates the hidden layers.
/// </summary>
IEnumerable<IEnumerable<Neuron>> CreateHiddenLayers()
{
var hiddenLayers = new List<IEnumerable<Neuron>>();
for (int i=0; i<_numHiddenLayers; i++)
{
var hiddenNodes = new List<Neuron>();
for (int j=0; j<_numNeuronsPerHiddenLayer; j++)
{
var neuron = new MlpNeuron(new List<Connection>(), new List<Connection>(), FunctionType.Sigmoid);
hiddenNodes.Add(neuron);
Neurons.Add(neuron);
}
hiddenNodes.Add(new BiasNode());
hiddenLayers.Add(hiddenNodes);
}
return hiddenLayers;
}
