Installing XGBoost on Ubuntu
XGBoost is the flavour of the moment for serious competitors on kaggle. It was developed by Tianqi Chen and provides a particularly efficient implementation of the Gradient Boosting algorithm. Although there is a CLI implementation of XGBoost you’ll probably be more interested in using it from either R or Python. Below are instructions for getting it installed for each of these languages. It’s pretty painless.
Installing for R
Installation in R is extremely simple.
It’s also supported as a model in caret, which is especially handy for feature selection and model parameter tuning.
Installing for Python
This might be as simple as
If you run into trouble with that, try the alternative approach below.
And you’re ready to roll:
If you run into trouble during the process you might have to install a few other packages:
Enjoy building great models with the absurdly powerful tool. I’ve found that it effortlessly consumes vast data sets that grind other algorithms to a halt. Get started by looking at some code examples. Also worth looking at are