public TraintimeEngine(int id, NeuralNetwork nn, StringCollection listOfInputAttributes, string outputAttribute) { _RuntimeEngine = new RuntimeEngine(id, nn, listOfInputAttributes); _ListOfInputAttributes = listOfInputAttributes; _OutputAttribute = outputAttribute; _NeuralNetwork = nn; }
public ValidationEngine(int id, NeuralNetwork neuralNetwork, List <string> listOfInputAttributes, string outputAttribute, float predictionThreshold, float positivePredictionLimit, float negativePredictionLimit) { ID = id; _NeuralNetwork = neuralNetwork; _ListOfInputAttributes = listOfInputAttributes; _OutputAttribute = outputAttribute; _RuntimeEngine = new RuntimeEngine(1, neuralNetwork, listOfInputAttributes); _MCCCalculator = new MatthewsCorrelationCoefficientCalculator(predictionThreshold, positivePredictionLimit, negativePredictionLimit); }
public TraintimeEngine(int id, NeuralNetwork nn, List <string> listOfInputAttributes, string outputAttribute, float momentum, float predictionThreshold, float positivePredictionLimit, float negativePredictionLimit) { _RuntimeEngine = new RuntimeEngine(id, nn, listOfInputAttributes); _ListOfInputAttributes = listOfInputAttributes; _OutputAttribute = outputAttribute; _NeuralNetwork = nn; _NeuronErrorDictionary = new Dictionary <int, float>(); foreach (Neuron neuron in _NeuralNetwork._ListOfNeurons) { _NeuronErrorDictionary.Add(neuron.ID, 0.00f); } _MCCCalculator = new MatthewsCorrelationCoefficientCalculator(predictionThreshold, positivePredictionLimit, negativePredictionLimit); _Momentum = momentum; _PreviousWeightDictionary = new Dictionary <int, float>(); foreach (SynapticConnection synaptic in _NeuralNetwork._ListOfSynapticConnections) { _PreviousWeightDictionary.Add(synaptic.ID, 0.00f); } }