public Train(NN nn, double[,] trainingInputs, double[,] trainingOutputs)
{
//if (trainingInputs.GetLength(0) != trainingOutputs.GetLength(0))
// throw new Exception();
//for (int i = 0; i < trainingInputs.GetLength(0); i++)
// nn.FeedForward(trainingInputs[i]);
// input[i] = trainingInputs[iter, i];
//double[] output = new double[trainingOutputs.GetLength(1)];
//for (int i = 0; i < output.GetLength(0); i++)
// input[i] = trainingOutputs[iter, i];
//nn.FeedForward(input);
//nn.BackPropogate(output);
}
public NNDebug()
{
NN nn = new NN(new int[] { 2, 3, 1 });
double[,] inputs = new double[4, 2]
{
{ 0, 0 },
{ 0, 1 },
{ 1, 0 },
{ 1, 1 }
};
double[,] outputs = new double[4, 1]
{
{ 0 },
{ 0 },
{ 1 },
{ 1 }
};
Console.WriteLine(nn);
new Train(nn, inputs, outputs);
}