public void Learn(TeachingElement element)
{
forwardPropagate(element);
backPropagate(element);
GlobalError = countGlobalError(_outputLayer.Errors);
}
private List <double> forwardPropagate(TeachingElement element)
{
List <double> inputResponse = layerResponse(_inputLayer, element.Inputs);
List <double> hiddenResponse = hiddenLayersResponse(inputResponse);
List <double> outputResponse = layerResponse(_outputLayer, hiddenResponse);
return(outputResponse);
}
public int Test(Bitmap image)
{
TeachingElement element = _parser.CreateTeachingElementFromImage(image, 2);
var output = _network.Test(element);
return((int)output);
}
public double Test(TeachingElement element)
{
List <double> outputResponse = forwardPropagate(element);
var sortedOutputResponse = new List <double>(outputResponse);
sortedOutputResponse.Sort();
sortedOutputResponse.Reverse();
return(outputResponse.IndexOf(sortedOutputResponse.First()));
}
private void backPropagate(TeachingElement element)
{
_outputLayer.SetOuputNeuronsError(element.ExpectedOutputs);
propagateErrorThroughLayers();
adjustWeights();
}
