public void AddEntry(TrainingSetEntry i_Entry)
{
bool checkInputSize = (m_Entries.Count > 0);
if (checkInputSize)
{
if (i_Entry.inputCount != entryInputSize)
{
return;
}
}
m_Entries.Add(i_Entry);
}
// INTERNALS
private void Train(ANN i_ANN, TrainingSet i_TrainingSet)
{
if (i_ANN == null || i_TrainingSet == null)
{
return;
}
if (i_ANN.ANNInputCount != i_TrainingSet.entryInputSize)
{
return;
}
for (int epoch = 0; epoch < m_EpochToTrain; ++epoch)
{
for (int trainingSetEntryIndex = 0; trainingSetEntryIndex < i_TrainingSet.entryCount; ++trainingSetEntryIndex)
{
TrainingSetEntry trainingSetEntry = i_TrainingSet.GetEntry(trainingSetEntryIndex);
if (trainingSetEntry == null)
{
continue;
}
float[] inputs = new float[trainingSetEntry.inputCount];
for (int inputIndex = 0; inputIndex < inputs.Length; ++inputIndex)
{
inputs[inputIndex] = trainingSetEntry.GetInput(inputIndex);
}
float[] desiredOutputs = new float[trainingSetEntry.outputCount];
for (int outputIndex = 0; outputIndex < desiredOutputs.Length; ++outputIndex)
{
desiredOutputs[outputIndex] = trainingSetEntry.GetOutput(outputIndex);
}
float[] outputs;
bool ANNRunSuccess = i_ANN.TryRun(inputs, out outputs);
ANNFunctionLibrary.AdjustWeights(i_ANN, desiredOutputs);
}
}
}
