public void Train(double[] input, double[] real)
{
var output = Calculate(input);
if (output.Length != real.Length)
{
throw new Exception("[NeuralNetwork.Train] output.Length != real.Length.");
}
var loss = _lossFunction.DifferentialExecute(output, real);
Layers.Last().CalculateLoss(loss);
for (int i = Layers.Count - 2; i >= 0; i--)
{
Layers[i].CalculateLoss(Layers[i + 1]);
}
for (int i = Layers.Count - 1; i > 0; i--)
{
Layers[i].Train(Layers[i - 1], _learnRate);
}
}
