| public Randomize ( double d ) : double | ||
| d | double | The range randomizer ignores this value. |
| Résultat | double | |
/// <summary>
/// Randomize the connections between two layers.
/// </summary>
/// <param name="network">The network to randomize.</param>
/// <param name="fromLayer">The starting layer.</param>
private void RandomizeSynapse(BasicNetwork network, int fromLayer)
{
int toLayer = fromLayer + 1;
int toCount = network.GetLayerNeuronCount(toLayer);
int fromCount = network.GetLayerNeuronCount(fromLayer);
int fromCountTotalCount = network.GetLayerTotalNeuronCount(fromLayer);
IActivationFunction af = network.GetActivation(toLayer);
double low = CalculateRange(af, Double.NegativeInfinity);
double high = CalculateRange(af, Double.PositiveInfinity);
double b = 0.7d * Math.Pow(toCount, (1d / fromCount)) / (high - low);
for (int toNeuron = 0; toNeuron < toCount; toNeuron++)
{
if (fromCount != fromCountTotalCount)
{
double w = RangeRandomizer.Randomize(-b, b);
network.SetWeight(fromLayer, fromCount, toNeuron, w);
}
for (int fromNeuron = 0; fromNeuron < fromCount; fromNeuron++)
{
double w = RangeRandomizer.Randomize(0, b);
network.SetWeight(fromLayer, fromNeuron, toNeuron, w);
}
}
}
/// <summary>
/// Makes random inputs by randomizing with encog randomize , the normal random from net framework library.
/// a quick and easy way to test data and and train networks.
/// </summary>
/// <param name="number">The number.</param>
/// <returns></returns>
public static double[] MakeRandomInputs(int number)
{
var rdn = new Random();
var encogRnd = new RangeRandomizer(-1, 1);
var x = new double[number];
for (int i = 0; i < number; i++)
{
x[i] = encogRnd.Randomize((rdn.NextDouble()));
}
return x;
}
