A Python library for replacing the missing variation in your text data
copied from cf-staging / niacinData collected for model training necessarily undersamples the likely variance in the input space. This library is a collection of tools for inserting typical kinds of perturbations to better approximate population variance; and, for creating similar-but-incorrect examples to aid in reducing the total size of the hypothesis space.
