/// <summary>
///
/// </summary>
/// <param name="input"></param>
/// <param name="hiddenLayerAmount"></param>
/// <param name="outLayerAmount"></param>
/// <param name="learningRate"></param>
public MultiLayerPerceptronNetwork(double[] input, int hiddenLayerAmount, int outLayerAmount, double learningRate)
{
Input = input;
LearningRate = learningRate;
// Allocating Hidden Layer
HiddenLayer = new Neuron[ hiddenLayerAmount ];
// Instantiating Neurons from Hidden Layer
for (int i = 0; i < HiddenLayer.Length; i++)
HiddenLayer[i] = new Neuron(Input.Length, LearningRate);
//
// Allocating Output Layer
OutLayer = new Neuron[ outLayerAmount ];
// Instantiating Neurons from Output Layer
for (int i = 0; i < OutLayer.Length; i++)
OutLayer[i] = new Neuron(HiddenLayer.Length, LearningRate);
//
// Setting Weights
SortWeights();
//SetManuallyWeights();
// Set input on the hidden layer
SetInputOnHiddenLayer();
}
// ------------------- 2.CONSTRUCTORS -------------------
/// <summary>
///
/// </summary>
/// <param name="hiddenLayerAmount">Quantidade de neurônios na camada oculta</param>
/// <param name="outLayerAmount">Quantidade de neurônios na camada de saída</param>
/// <param name="learningRate">Taxa de aprendizado</param>
public MultiLayerPerceptronNetwork(int inputAmount, int hiddenLayerAmount, int outLayerAmount, double learningRate)
{
LearningRate = learningRate;
// Allocating Input Layer
Input = new double[inputAmount];
// Allocating Hidden Layer
HiddenLayer = new Neuron[hiddenLayerAmount];
// Instantiating Neurons from Hidden Layer
for (int i = 0; i < HiddenLayer.Length; i++)
HiddenLayer[i] = new Neuron(Input.Length, LearningRate);
//
// Allocating Output Layer
OutLayer = new Neuron[outLayerAmount];
// Instantiating Neurons from Output Layer
for (int i = 0; i < OutLayer.Length; i++)
OutLayer[i] = new Neuron(HiddenLayer.Length, LearningRate);
//
// Setting Weights
SortWeights();
}
