public Neuron(Vector <double> initialWeights, double bias, double initialBiasWeight, Delegates.ActivationFunction activationFunction)
{
Weights = initialWeights;
Bias = bias;
BiasWeight = initialBiasWeight;
_activationFunction = activationFunction;
}
private void SetDerivativeFunctionType(Delegates.ActivationFunction activationFunction)
{
if (activationFunction == Functions.SigmoidBipolar)
{
_derivativeFunction = Functions.SigmoidBipolarDerivative;
}
else
{
_derivativeFunction = Functions.SigmoidUnipolarDerivative;
}
}
public Layer(int numberOfNeurons, int numberOfInputs, Delegates.ActivationFunction activationFunction, Randomizer randomizer)
{
Neurons = new List <Neuron>();
for (int index = 0; index < numberOfNeurons; index++)
{
const double bias = 1.0;
var initialWeights = randomizer.RandomizeWeights(numberOfInputs);
var initialBiasWeight = randomizer.RandomizeBias();
Neurons.Add(new Neuron(initialWeights, bias, initialBiasWeight, activationFunction));
}
}
public MultiLayerPerceptron(int numberOfLayers, List <int> inputsPerLayer, List <int> neuronsPerLayer, Delegates.ActivationFunction activationFunction)
{
_randomizer = new Randomizer();
_layers = new List <Layer>();
_dataReader = new DataReader();
for (int index = 0; index < numberOfLayers; index++)
{
_layers.Add(new Layer(neuronsPerLayer[index], inputsPerLayer[index], activationFunction, _randomizer));
}
SetDerivativeFunctionType(activationFunction);
}
