private void SetActivationFunction(ActivationFunction.Functions function)
{
foreach (Layer l in Layers)
{
l.SetActivationFunction(function);
}
}
public NeuralNetwork(int totalInputNodes, int totalHiddenLayers, int totalHiddenNodes, int totalOutputNodes, ActivationFunction.Functions function)
{
TotalInputNodes = totalInputNodes;
TotalHiddenLayers = totalHiddenLayers;
TotalHiddenNodes = totalHiddenNodes;
TotalOutputNodes = totalOutputNodes;
learningRate = 0.0075;
CreateLayers();
SetActivationFunction(function);
VisualSetup();
}
public NeuralNetwork(int totalInputNodes, int totalHiddenLayers, int totalHiddenNodes, int totalOutputNodes, ActivationFunction.Functions function) : this(totalInputNodes, totalHiddenLayers, totalHiddenNodes, totalOutputNodes)
{
SetActivationFunction(function);
}
public void SetActivationFunction(ActivationFunction.Functions function)
{
ActivationFunction = new ActivationFunction(function);
}
public NeuralNetwork(double[,] WeightsInputToHidden, double[,] WeightsHiddenToOutput, double[,] BiasHidden, double[,] BiasOutput, ActivationFunction.Functions function)
{
TotalInputNodes = WeightsInputToHidden.GetLength(1);
TotalHiddenNodes = WeightsInputToHidden.GetLength(0);
TotalOutputNodes = WeightsHiddenToOutput.GetLength(0);
this.WeightsInputToHidden = Matrix <double> .Build.DenseOfArray(WeightsInputToHidden);
this.WeightsHiddenToOutput = Matrix <double> .Build.DenseOfArray(WeightsHiddenToOutput);
this.BiasHidden = Matrix <double> .Build.DenseOfArray(BiasHidden);
this.BiasOutput = Matrix <double> .Build.DenseOfArray(BiasOutput);
ActivationFunction = new ActivationFunction(function);
VisualSetup();
}
