public void ShowWeights()
{
for (int layerCount = 0; layerCount < LayerCount(); layerCount++)
{
FeedForwardNetLayer currentLayer = GetLayer(layerCount);
for (int fromNo = 0; fromNo < currentLayer.GetFromUnitCount(); fromNo++)
{
Console.WriteLine("act layer {0} fromNo {1} = {2} ", layerCount, fromNo, currentLayer.GetFromUnitActivation(fromNo).ToString());
}
for (int toNo = 0; toNo < currentLayer.GetToUnitCount(); toNo++)
{
Console.WriteLine("act layer {0} toNo {1} = {2} ", layerCount, toNo, currentLayer.GetToUnitActivation(toNo).ToString());
}
for (int toNo = 0; toNo < currentLayer.GetToUnitCount(); toNo++)
{
for (int fromNo = 0; fromNo < currentLayer.GetFromUnitCount(); fromNo++)
{
Console.WriteLine("layer {0} From {1} To {2} Weight {3}", layerCount, fromNo, toNo, currentLayer.GetLayerWeight(fromNo, toNo).ToString());
}
Console.WriteLine("layer {0} To {1} bias {2} ", layerCount, toNo, currentLayer.GetLayerBias(toNo).ToString());
Console.WriteLine("--------");
}
}
}
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));
}
}
ErrorMeasure ForwardPassError(ITrainingSetItemRepository trainingSetItem)
{
ErrorMeasure errorMeasure;
double sumError = 0.0;
double localError;
Boolean hasLearned = true;
FeedForwardNetLayer outputLayer = feedForwardNet.GetOutputLayer();
for (int outputNo = 0; outputNo < outputLayer.GetToUnitCount(); outputNo++)
{
localError = Math.Abs(trainingSetItem.GetOutputNodeValue(outputNo) - outputLayer.GetToUnitActivation(outputNo));
if (localError > backPropagationConstants.OutputTolerance)
{
hasLearned = false;
}
sumError += localError;
}
errorMeasure = new ErrorMeasure(hasLearned, sumError);
return(errorMeasure);
}
