2 Note that at test time, most of the h tokens will have been seen before in the training data (due to Zipf's law), and for these tokens it is very difficult to beat a baseline that normalizes each h to the most common m seen for it in training.
3 in practice, normalization systems should typically only be applied to unseen tokens.