An example of how to make Python’s XGBoost easily work in R

There’s no doubt that Python has the widest range of ML algorithms of all the programming languages and in general Python is my first port of call if I am intending to do any form of predictive modeling. That said, I much prefer R for the tidying and preparation of data and would love to be able to import Python algorithms into R so I can have the best of both worlds. So I recently decided to see if I could easily run a Python ML algorithm in R. I opted to try a k-fold cross-validated XGBoost model.

I determined that it was pretty easy to do this working in RStudio, so I’ve written up the ‘how’ here. I also put together a Github repo with this example.

#python #programming #data-science #machine-learning #r-programming