I'm new to Neural Networks. Trying to get some general advice.
Multi Class, 3 classes
Has noisy labels, with somewhere between 60 and 80 percent accuracy
Huge amount of training with the issues mentioned
Classes known to follow a roughly 3:2:1 distribution in terms of abundance
Feature Space has the ability to overfit if too much interaction allowed
Features have some noise as well, enough not to easily yield to linear decomposition
I've used neuralnet and now using ANN2, mainly due to having regularization exposed. I've attempted to denoise the labels with an ensemble denoising procedure found in NoiseFiltersR with some success. If it weren't for the noisy labels, what I'm trying to do would have been done a hundred times over.
Would like some advice relating to:
Recommended Neural Network Architecture, especially as it relates to the noisy labels.