public override void Fit(double[,] Xtrain, int[,] Ytrain, int epochs, double learningRate, double lambda)
{
var amountOfExamples = Xtrain.GetLength(0);
int iteration = 0;
double cost = 0;
List <double[]> actualOutputs = new List <double[]>(Ytrain.GetLength(0));
while (iteration < epochs)
{
iteration++;
for (var i = 0; i < Xtrain.GetLength(0); i++)
{
Feedforward(Xtrain.GetRow(i));
var output = Backpropagate(Ytrain.GetRow(i));
actualOutputs.Add(output);
if (i % 5000 == 0)
{
Console.WriteLine("Epoch: {0} step {1}/total {2}", iteration, i, amountOfExamples);
}
}
// update weights and biases
optimizer.Run(layers, learningRate, lambda, Xtrain.GetLength(0));
Clear();
// calculate of cost function value
try
{
if (regularization != null)
{
var term1 = costFunction.Function(Ytrain, actualOutputs);
var reg = regularization(lambda, amountOfExamples, layers);
cost = term1 + reg;
}
else
{
throw new InvalidOperationException("The regularization have not been defined.");
}
}
catch (Exception) { }
actualOutputs.Clear();
Console.WriteLine("Epoch: {0}, cost {1} ", iteration, cost);
}
}
