public virtual void Learn(CY_NN_Dataset set, int trainingEpochs)
{
isStopping = false;
Initialize();
for (int currentIteration = 0; currentIteration < trainingEpochs; currentIteration++)
{
int[] randomOrder = GetRandomOrder(set.trainingSamples.Count);
OnBeginEpoch(currentIteration, set);
if (jitterEpoch > 0 && currentIteration % jitterEpoch == 0)
{
for (int i = 0; i < connectors.Count; i++)
{
connectors[i].noise(jitterNoiseLimit);
}
}
for (int index = 0; index < set.trainingSamples.Count; index++)
{
CY_NN_Dataset_Entry e = set[randomOrder[index]];
OnBeginSample(currentIteration, e);
LearnSample(set[randomOrder[index]], currentIteration, trainingEpochs);
OnEndSample(currentIteration, e);
if (isStopping)
{
isStopping = false; return;
}
}
OnEndEpoch(currentIteration, set);
if (isStopping)
{
isStopping = false; return;
}
}
}
protected virtual void OnEndEpoch(int currentIteration, CY_NN_Dataset set)
{
if (EndEpochEvent != null)
{
EndEpochEvent(this, new CY_Dataset_Epoch_Args(currentIteration, set));
}
}
protected override void OnEndEpoch(int i, CY_NN_Dataset set)
{
mse /= set.trainingSamples.Count;
base.OnEndEpoch(i, set);
}
protected override void OnBeginEpoch(int i, CY_NN_Dataset set)
{
mse = 0d;
base.OnBeginEpoch(i, set);
}
public CY_Dataset_Epoch_Args(int trainingIteration, CY_NN_Dataset set)
{
this.set = set;
this.i = trainingIteration;
}
