fixed the bugs with MNIST.py - need the features to be in range [0,1], otherwise we get underflow issues in the softmax computation - also, updated scipy, so we can now specify the number of iterations for conjugate gradient and l-bfgs. next commit will start doing pre-training to improve classification. 3-layer net on MNIST with 50 hidden units using 100 iterations of lbfgs gives an error rate of ~ 2%. Curious to see how much more pre-training will improve results