/**
* Initialize back propagator with the appropriate settings
*
* @return an initialized BackPropagator
* @throws Exception
*/
private BackPropagator initializeTrainer() throws Exception {
BackPropagator trainer = new BackPropagator(_network, _learningRate);
int trainingCount = _trainingSet.getCount();
for (int i = 0; i < trainingCount; i++) {
TrainingGrid t = _trainingSet.getGrid(i);
trainer.addInputOutput(
GridProcessor.convertGrid(t.getGrid()),
GridProcessor.convertExpectedOutput(t.getValue()));
}
return trainer;
}
/**
* Train the set Network with the set TrainingSet and learning rate for the set EpochCount times
*/
@Override
public Void doInBackground() {
try {
int progress = 0;
BackPropagator trainer = initializeTrainer();
setProgress(0);
while (progress < _epochCount && !isCancelled()) {
trainer.runAndUpdate();
progress++;
setProgress((100 * progress) / _epochCount);
}
} catch (Exception ex) {
ex.printStackTrace();
}
return null;
}
