public double RunEpoch(double[][] input)
{
double error = 0.0;
double[][] data = new double[input.Length][];
for (int i = 0; i < data.Length; i++)
{
data[i] = (double[])input[i].Clone();
}
for (int i = 0; i < rbm_learnings.Length; i++)
{
Console.WriteLine(i);
RBMLayer rbm = dbn.Layers[i];
rbm_learnings[i] = new RBMLearning(rbm);
for (int j = 0; j < epoch; j++)
{
rbm_learnings[i].RunEpoch(data);
}
for (int j = 0; j < input.Length; j++)
{
data[j] = rbm.ComputeDown(data[j]);
}
}
return(error);
}
public RBMLearning(RBMLayer rbm)
{
this.rbm = rbm;
Q = new double[rbm.InputsCount];
P = new double[rbm.NeuronsCount];
random = new Random((int)DateTime.Now.Ticks);
}
public DBNNetwork(IActivationFunction function, int inputsCount, params int[] neuronsCount)
: base(inputsCount, neuronsCount.Length)
{
for (int i = 0; i < LayersCount; i++)
{
layers[i] = new RBMLayer(
neuronsCount[i],
(i == 0) ? inputsCount : neuronsCount[i - 1],
function);
}
}
