public async Task RunFeedbackPhaseAsync(IEnumerable <double> idealValues)
{
await _errorValueBackPropagator.BackPropagateAllErrorsAsync(Perceptron.GetOutputUnits(), idealValues);
// Most authors give examples that update weights from the inputs forward, but the end result is no different when we work from outputs backwards
// and from an implementation point of view it is simpler to start with our outputs which we needed for the error calculations
await _weightChangeBackPropagator.UpdateAllWeightsAsync();
}
public IEnumerable <ITraversableUnitReadOnly <IUnitUnderTraining, IConnectionUnderTraining, IUnitActivationTraining> > GetOutputUnits()
{
return(_perceptronUnderTraining.GetOutputUnits());
}