public Network BuildNetwork()
{
for (int i = 0; i < _inputNodeInitialCount; i++)
{
var inputNode = new InputNode(i);
_inputNodes.Add(inputNode);
}
for (int i = 0; i < _outPutNodeInitialCount; i++)
{
var outputNode = new OutputNode(i, _activationFunction, _weightAdjustFunction);
_outputNodes.Add(outputNode);
}
for (int i = 0; i < _hiddenLayerInitialCount; i++)
{
_hiddenNodes[i] = new List <HiddenNode>();
for (int j = 0; j < _hiddenNodePerLayerInitialCount; j++)
{
_hiddenNodes[i].Add(new HiddenNode(j, _activationFunction, _weightAdjustFunction, _getRandom));
}
if (i == 0)
{
_hiddenNodes[i].ForEach((o) =>
{
o.AddInputNodes(_inputNodes);
});
}
else
{
_hiddenNodes[i].ForEach((o) =>
{
o.AddInputNodes(_hiddenNodes[i - 1]);
});
}
}
_outputNodes.ForEach((o) =>
{
if (_hiddenLayerInitialCount == 0 || _hiddenNodePerLayerInitialCount == 0)
{
o.AddInputNodes(_inputNodes);
}
else
{
o.AddInputNodes(_hiddenNodes[_hiddenLayerInitialCount - 1]);
}
});
return(this);
}
public NeuralGeneNode AddOutputNode(NeuralActivationFunction _neuralActivationFunctions)
{
if (OutputLayer == null)
{
OutputLayer = new List <NeuralGeneNode>();
}
if (nodes == null)
{
nodes = new List <NeuralGeneNode>();
}
NeuralGeneNode tmpNode = new NeuralGeneNode(_neuralActivationFunctions, nodes.Count + 1, NeuralNodeType.Output);
OutputLayer.Add(tmpNode);
nodes.Add(tmpNode);
return(tmpNode);
}
public void AddOutputsNode(int _outputSize, NeuralActivationFunction _neuralActivationFunctions)
{
if (OutputLayer == null)
{
OutputLayer = new List <NeuralGeneNode>();
}
if (nodes == null)
{
nodes = new List <NeuralGeneNode>();
}
for (int i = 0; i < _outputSize; i++)
{
NeuralGeneNode tmpNode = new NeuralGeneNode(_neuralActivationFunctions, nodes.Count + 1, NeuralNodeType.Output);
OutputLayer.Add(tmpNode);
nodes.Add(tmpNode);
}
}
AddNeuralLayer(int countNeurons,
double initialWeight) //public NeuralLayer(int count, double initialWeight, string name = "")
{
OutputLayer.Add(new List <Neuron>());
var lastIndex = OutputLayer.Count - 1;
weightsLayouts.Add(initialWeight);
for (var i = 0; i < countNeurons; i++)
{
OutputLayer[lastIndex].Add(new Neuron(lastIndex, i, OutputLayer.Count));
OutputLayer[lastIndex][i].Weights = new List <double>(InputLayerDimension);
for (var k = 0; k < Patterns[0].Count; k++)
{
OutputLayer[lastIndex][i].Weights.Add(initialWeight);
}
}
AddDendritesToAllLayers();
}
