public StochasticGradientDescent(IActivationFunction hiddenActivationFunction, IActivationFunction outputActivationFunction, ICostFunction costFunction,
RegularizationType regularizationType, IRegularizationStrategyFactory regularizationStrategyFactory)
{
_hiddenActivationFunction = hiddenActivationFunction;
_outputActivationFunction = outputActivationFunction;
_costFunction = costFunction;
_regularizationType = regularizationType;
_regularizationStrategyFactory = regularizationStrategyFactory; //would normally solve this with IOC
}
public IRegularizationStrategy CreateRegularizationStrategy(RegularizationType regularizationType)
{
switch (regularizationType)
{
case RegularizationType.L1:
return(new L1());
case RegularizationType.L2:
return(new L2());
case RegularizationType.None:
return(new NoRegularization());
default:
return(new L2());
}
}
public INetwork LoadNetwork(string xmlFilePath, IDataSet dataset)
{
_xmlDoc = new XmlDocument();
_filepath = xmlFilePath;
_xmlDoc.Load(_filepath);
//Create Training Params---------------------8::::::::::::::>----------------------------------------
TrainingParameters trainingParams = new TrainingParameters()
{
epochs = Convert.ToInt32(GetXmlValue("NeuralNetwork/Settings/TrainingParameters/Epochs")),
learningRate = Convert.ToDouble(GetXmlValue("NeuralNetwork/Settings/TrainingParameters/LearningRate")),
momentum = Convert.ToDouble(GetXmlValue("NeuralNetwork/Settings/TrainingParameters/Momentum"))
};
//Create LayerStructure---------------------8::::::::::::::>----------------------------------------
List <int> hiddenLayersList = new List <int>();
int numberOfHiddenLayers = Convert.ToInt32(GetXmlValue("NeuralNetwork/Settings/LayerStructure/NumberOfHiddenLayers"));
for (int i = 1; i <= numberOfHiddenLayers; i++)
{
int numberOfNeuronsInHiddenLayer = Convert.ToInt32(GetXmlValue("NeuralNetwork/Settings/LayerStructure/NumberOfNeuronsInHiddenLayer" + i.ToString()));
hiddenLayersList.Add(numberOfNeuronsInHiddenLayer);
}
LayerStructure layerStructure = new LayerStructure()
{
numberOfInputNodes = Convert.ToInt32(GetXmlValue("NeuralNetwork/Settings/LayerStructure/NumberOfInputNeurons")),
numberOfOutputNodes = Convert.ToInt32(GetXmlValue("NeuralNetwork/Settings/LayerStructure/NumberOfOutputNeurons")),
HiddenLayerList = hiddenLayersList
};
//Create Distribution Type---------------------8::::::::::::::>----------------------------------------
string distribution = GetXmlValue("NeuralNetwork/Settings/DistributionType/InitialRandomDistributionType");
var distributionType = Type.GetType(distribution + ",NeuralNetwork.Core");
IInitialRandomDistributionType initialDistribution = Activator.CreateInstance(distributionType) as IInitialRandomDistributionType;
//Create Strategy---------------------8::::::::::::::>----------------------------------------
string hiddenFunction = GetXmlValue("NeuralNetwork/Settings/Strategy/HiddenLayerActivationFunction");
string outputFunction = GetXmlValue("NeuralNetwork/Settings/Strategy/OutputLayerActivationFunction");
string costFunc = GetXmlValue("NeuralNetwork/Settings/Strategy/CostFunction");
string regularizationEnum = GetXmlValue("NeuralNetwork/Settings/Strategy/RegularizationType");
string regularizationStrategyFactory = GetXmlValue("NeuralNetwork/Settings/Strategy/RegularizationStrategyFactory");
var hiddenFunctionType = Type.GetType(hiddenFunction + ",NeuralNetwork.Core");
var outputFunctionType = Type.GetType(outputFunction + ",NeuralNetwork.Core");
var costFunctionType = Type.GetType(costFunc + ",NeuralNetwork.Core");
var regularizationStrategyFactoryType = Type.GetType(regularizationStrategyFactory + ",NeuralNetwork.Core");
IActivationFunction hiddenActivationFunction = Activator.CreateInstance(hiddenFunctionType) as IActivationFunction;
IActivationFunction outputActivationFunction = Activator.CreateInstance(outputFunctionType) as IActivationFunction;
ICostFunction costFunction = Activator.CreateInstance(costFunctionType) as ICostFunction;
RegularizationType regularizationType = (RegularizationType)Enum.Parse(typeof(RegularizationType), regularizationEnum);
IRegularizationStrategyFactory regularizationStrategyFact = Activator.CreateInstance(regularizationStrategyFactoryType) as IRegularizationStrategyFactory;
string optimizationStrategy = GetXmlValue("NeuralNetwork/Settings/Strategy/OptimizationStrategy");
var optStrategy = Type.GetType(optimizationStrategy + ",NeuralNetwork.Core");
IOptimizationStrategy strategy = Activator.CreateInstance(optStrategy, hiddenActivationFunction, outputActivationFunction, costFunction, regularizationType, regularizationStrategyFact) as IOptimizationStrategy;
//Create Network---------------------8::::::::::::::>----------------------------------------
network = new ArtificialNeuralNetwork(layerStructure, trainingParams, dataset, strategy, initialDistribution);
//Set Weights---------------------8::::::::::::::>----------------------------------------
network.Weights.Clear();
LoadInputWeights();
LoadHiddenWeights();
//Set Biases---------------------8::::::::::::::>----------------------------------------
network.Biases.Clear();
LoadHiddenBiases();
LoadOutputBiases();
//Clear XMLDoc---------------------8::::::::::::::>----------------------------------------
_xmlDoc = null;
return(network);
}
