public BackPropagationTrainer(IFeedForwardNetRepository feedForwardNet, IBackPropagationConstants backPropagationConstants, ISquashFunction squashFunction,
ITrainingSetRepository trainingSet,
IHiddenLayerWeightChangeStrategy hiddenUnitWeightStrategy,
IOutputLayerWeightChangeStrategy outputUnitWeightStrategy)
{
this.feedForwardNet = feedForwardNet;
this.backPropagationConstants = backPropagationConstants;
this.squashFunction = squashFunction;
this.trainingSet = trainingSet;
this.hiddenUnitWeightStrategy = hiddenUnitWeightStrategy;
this.outputUnitWeightStrategy = outputUnitWeightStrategy;
}
public void FeedForwardPass(ISquashFunction squashFunction, ITrainingSetItemRepository trainingSetItem)
{
FeedForwardNetLayer currentLayer;
FeedForwardNetLayer previousLayer;
for (int currentLayerNo = 0; currentLayerNo < LayerCount(); currentLayerNo++)
{
currentLayer = GetLayer(currentLayerNo);
if (currentLayerNo > 0)
{
previousLayer = GetLayer(currentLayerNo - 1);
}
else
{
previousLayer = null;
}
SetLayerActivation(ref currentLayer, trainingSetItem, previousLayer, currentLayerNo);
CalculateNewLayerActivation(ref currentLayer, squashFunction);
}
//return ForwardPassError(trainingSetItem, currentLayerNo);
}
public void CalculateNewLayerActivation(ref FeedForwardNetLayer currentLayer, ISquashFunction squashFunction)
{
double weightSum;
for (int toNo = 0; toNo < currentLayer.GetToUnitCount(); toNo++)
{
weightSum = 0.0;
for (int fromNo = 0; fromNo < currentLayer.GetFromUnitCount(); fromNo++)
{
weightSum += currentLayer.GetFromUnitActivation(fromNo) * currentLayer.GetLayerWeight(fromNo, toNo);
}
weightSum += currentLayer.GetLayerBias(toNo);
currentLayer.SetToUnitActivation(toNo, squashFunction.Squash(weightSum));
}
}
