private double trainOneEpochWithLogging(bool WriteToDataBase)
{
this.epoch++;
double[] sumOfAbsoluteErrors = new double[outputLayer.getNeurons().Count()];
double[] sumOfErrors = new double[outputLayer.getNeurons().Count()];
for (int i = 0; i < outputLayer.getNeurons().Count(); i++)
{
sumOfAbsoluteErrors[i] = 0f;
}
for (int i = 0; i < this.trainingsset.inputs.Length; i++) //Loop over every input dataset
{
setInputs(this.trainingsset.inputs[i]);
this.fire();
calculateErrors(this.trainingsset.results[i]);
this.asjustWeights();
double[] betw = outputLayer.getAbsoluteErrors();
sumOfAbsoluteErrors = sumOfAbsoluteErrors.Zip(betw, (x, y) => x + y).ToArray <double>();
}
sumOfAbsoluteErrors = sumOfAbsoluteErrors.Select(d => d / this.trainingsset.inputs.Length).ToArray <double>();// divide by the amount of trainings-inmputs, so we get the average error for every outputneuron
if (WriteToDataBase)
{
DBHelper.HandleInsert(DatabaseID, sumOfAbsoluteErrors, epoch);
}
print(sumOfAbsoluteErrors);
return(sumOfAbsoluteErrors.Sum());
}
