/// <summary>
/// Construct RBF network.
/// </summary>
///
/// <param name="inputCount">The input count.</param>
/// <param name="hiddenCount">The hidden count.</param>
/// <param name="outputCount">The output count.</param>
/// <param name="t">The RBF type.</param>
public RBFNetwork(int inputCount, int hiddenCount,
int outputCount, RBFEnum t)
{
if (hiddenCount == 0)
{
throw new NeuralNetworkError(
"RBF network cannot have zero hidden neurons.");
}
var rbf = new IRadialBasisFunction[hiddenCount];
// Set the standard RBF neuron width.
// Literature seems to suggest this is a good default value.
double volumeNeuronWidth = 2.0d / hiddenCount;
_flat = new FlatNetworkRBF(inputCount, rbf.Length, outputCount, rbf);
try
{
// try this
SetRBFCentersAndWidthsEqualSpacing(-1, 1, t, volumeNeuronWidth,
false);
}
catch (EncogError)
{
// if we have the wrong number of hidden neurons, try this
RandomizeRBFCentersAndWidths(-1, 1, t);
}
}
/// <summary>
/// Construct RBF network.
/// </summary>
///
/// <param name="inputCount">The input count.</param>
/// <param name="outputCount">The output count.</param>
/// <param name="rbf">The RBF type.</param>
public RBFNetwork(int inputCount, int outputCount,
IRadialBasisFunction[] rbf)
{
_flat = new FlatNetworkRBF(inputCount, rbf.Length, outputCount, rbf)
{
RBF = rbf
};
}
/// <summary>
/// Construct RBF network.
/// </summary>
///
public RBFNetwork()
{
_flat = new FlatNetworkRBF();
}
