private void TrainNetwork(ref NetworkTrainingParameters parameters)
{
ComputeOutputGradients(parameters.ExpectedResult, parameters.OutputGradients);
ComputeHiddenGradients(parameters.OutputGradients, parameters.HiddenGradients);
UpdateHiddenWeights(parameters.LeaningRate, parameters.Momentum, parameters.HiddenGradients);
UpdateHiddenBiases(parameters.LeaningRate, parameters.Momentum, parameters.HiddenGradients);
UpdateHiddenOutputWeights(parameters.LeaningRate, parameters.Momentum, parameters.OutputGradients);
UpdateOutputBiases(parameters.LeaningRate, parameters.Momentum, parameters.OutputGradients);
}
public void Train(NeuralNetworkTrainingData data)
{
var trainingParameters = new NetworkTrainingParameters(_numberOfOutputNodes, _numberOfHiddenNodes)
{
LeaningRate = data.LearnRate,
Momentum = data.Momentum
};
var inputVector = new double[_numberOfInputNodes];
for (var i = 0; i < data.MaxEpochs; i++)
{
var sequence = NeuralNetworkHelpers.Randomize(data.TrainingData.Length);
foreach(var index in sequence)
{
Array.Copy(data.TrainingData[index], inputVector, _numberOfInputNodes);
Array.Copy(data.TrainingData[index], _numberOfInputNodes, trainingParameters.ExpectedResult, 0, _numberOfOutputNodes);
ComputeOutputs(inputVector);
TrainNetwork(ref trainingParameters);
}
}
}