// Prediction layer //
public void AddPredictionLayer(FNodeSet Fields, ScalarFunction Activator, NodeReduction Reducer)
{
this._PredictionActivation = Activator;
this._YValues = Fields;
this._PredictionReducer = Reducer;
}
// Hidden layer //
public void AddHiddenLayer(bool Bias, int DynamicCount, ScalarFunction Activator, NodeReduction Reducer)
{
this._HiddenLayers.Add(new NN_Layer(Bias, Reducer, Activator, DynamicCount, this._HiddenLayers.Count + 1));
}
public void AddHiddenLayer(bool Bias, int DynamicCount, ScalarFunction Activator)
{
this.AddHiddenLayer(Bias, DynamicCount, Activator, this.DefaultReduction);
}
public NN_Layer(bool Bias, NodeReduction Connector, ScalarFunction Activator, int TotalCount, int Level)
: this()
{
// Check if rendered //
if (this._IsRendered)
throw new Exception("Layer already rendered");
// Check the total count //
if (TotalCount < 1)
throw new Exception("Cannot have fewer than one node");
// Add the bias node //
if (Bias)
this._Nodes.Add(new NeuralNodeStatic(string.Format("H{0}_0", Level), 1));
// Add the references //
for (int i = 0; i < TotalCount; i++)
this._Nodes.Add(new NeuralNodeDynamic(string.Format("H{0}_{1}", Level, i + 1), Activator, Connector));
// Tag as rendered //
this._IsRendered = true;
}
public NN_Layer(NodeReduction Connector, ScalarFunction Activator, Key Fields)
: this()
{
// Check if rendered //
if (this._IsRendered)
throw new Exception("Layer already rendered");
// Add the references //
for (int i = 0; i < Fields.Count; i++)
this._Nodes.Add(new NeuralNodePrediction("Y" + i.ToString(), Activator, Connector, Fields[i]));
// Tag as rendered //
this._IsRendered = true;
}
public void AddPredictionLayer(FNodeSet Fields, ScalarFunction Activator)
{
this.AddPredictionLayer(Fields, Activator, this.DefaultReduction);
}
public void AddOutputLayer(int[] Offsets, ScalarFunction Activator)
{
if (this._phase != 0)
throw new InvalidOperationException("Cannot alter the state of the network after it has been constructed");
this._terminis = new OutputLinearLayer(Offsets, Activator);
}
public void AddHiddenLayer(int Size, bool Bias, ScalarFunction Activator)
{
if (this._phase != 0)
throw new InvalidOperationException("Cannot alter the state of the network after it has been constructed");
DynamicLinearLayer layer = new DynamicLinearLayer(Size, Bias, Activator);
this._layer_tree.Add(layer);
}
public OutputLinearLayer(int[] Offsets, ScalarFunction Activation)
: base(Offsets.Length, false)
{
this.OFFSETS = Offsets;
this.ACT = Activation;
this.Affinity = NeuralLayerAffinity.Output;
}
public DynamicLinearLayer(int Size, bool Bias, ScalarFunction Activation)
: base(Size + (Bias ? 1 : 0), Bias)
{
this.ACT = Activation;
this.Affinity = NeuralLayerAffinity.Dynamic;
}