public NeuronalNetworkClassifier(List <Tuple <double[], double[]> > data,
int inputNeurons, int outputNeurons, int firstHiddenLayerNeurons,
int secondHiddenLayerNeurons, int thirdHiddenLayerNeurons, int evolutions = 1000, double learningRate = 0.5,
NeuronalNetworkMode neuronalNetworkMode = NeuronalNetworkMode.Standard)
{
var neuronCounter = new ThirdHiddenLayerNeuronCounter(inputNeurons, outputNeurons, firstHiddenLayerNeurons, secondHiddenLayerNeurons, thirdHiddenLayerNeurons);
this.data = data;
this.feedforwardNeuronalNetwork = new FeedforwardNeuronalNetwork(neuronCounter, evolutions, learningRate, neuronalNetworkMode);
}
public static NeuronalNetwork CreateInstance(NeuronalNetworkMode neuronalNetworkMode)
{
if (neuronalNetworkMode == NeuronalNetworkMode.Cascade)
{
return(new CascadeFeedforwardNetwork());
}
else if (neuronalNetworkMode == NeuronalNetworkMode.Dynamic)
{
return(new DynamicFeedforwardNetwork());
}
return(new FeedforwardNetwork());
}
public FeedforwardNeuronalNetwork(OneHiddenLayerNeuronCounter neuronCounter, int evolutions = 1000, double learningRate = 0.5,
NeuronalNetworkMode neuronalNetworkMode = NeuronalNetworkMode.Standard)
{
this.mode = NeuronalCounterMode.OneHiddenLayer;
this.neuronalNetworkMode = neuronalNetworkMode;
this.neuronCounter = neuronCounter;
this.evolutions = evolutions;
this.learningRate = learningRate;
this.inputValuesCount = neuronCounter.InputNeuronCount;
this.outputValuesCount = neuronCounter.OutputNeuronCount;
neuronalNetwork = NeuronalNetworkModeFactory.CreateInstance(neuronalNetworkMode);
this.neuronalNetwork.NeuronalNetworkMode = neuronalNetworkMode;
this.neuronalNetwork.AddInputLayer(new FeedforwardLayer(activationFunction, neuronCounter.InputNeuronCount, 0));
this.neuronalNetwork.AddHiddenLayer(new FeedforwardLayer(activationFunction, neuronCounter.FirstLayerHiddenNeuronCount, 1));
this.neuronalNetwork.AddOutputLayer(new FeedforwardLayer(activationFunction, neuronCounter.OutputNeuronCount, 2));
this.neuronalNetwork.LearningRate = learningRate;
this.neuronalNetwork.Evolutions = evolutions;
this.neuronalNetwork.RandomFillWeightMatrix();
}
