/// <summary>
/// Calculates the gradient.
/// </summary>
/// <param name="target">The target.</param>
/// <returns></returns>
public double CalculateGradient(double?target = null)
{
if (target == null)
{
return(Gradient = OutputSynapses.Sum(a => a.OutputNeuron.Gradient * a.Weight) * Sigmoid.Derivative(Value));
}
return(Gradient = CalculateError(target.Value) * Sigmoid.Derivative(Value));
}
public virtual double CalculateValue()
{
return(Value = Sigmoid.Output(InputSynapses.Sum(a => a.Weight * a.InputNeuron.Value) + Bias));
}
public virtual double CalculateHiddenValue()
{
return(Value = Sigmoid.Relu(InputSynapses.Sum(a => a.Weight * a.InputNeuron.Value)));
}
