1. A method for optimizing a training set comprised of a large plurality of training pairs for use in training a neural network, said method comprising the steps of: a) training a neural network using said training set; b) measuring a generalization error of the trained neural network; c) removing a training pair from the training set to produce a reduced training set; d) training the neural network using the reduced training set; e) measuring the generalization error of the trained reduced training set; f) reinserting the removed training pair into the training set; g) performing steps c), d), e), and f) above for each training pair in the training set; h) sorting the training pairs based on their measured generalization error; and i) performing steps c), d), e) and f) above for each training pair in the training set, except that said reinserting in step f) is not performed when the measured generalization error in step e) is less than that obtained before removal of the training pair.