Can numerical encoding really replace one-hot encoding?
I am reading these articles (see below), which advocate the use of numerical encoding rather than one hot encoding for better interpretability of feature importance output from ensemble models. This goes against everything I have learnt - won't Python treat nominal features (like cities, car make/model) as ordinal if I encode them into integers?
https://krbnite.github.io/The-Quest-for-Blackbox-Interpretability-Take-1/
Topic ensemble-learning one-hot-encoding preprocessing python
Category Data Science