XGBoost is probably the most cutting-edge and optimized implementation of the gradient boosting algorithms. If you’re a R user, you probably used GBM in the past. XGBoost is generally over 10 times faster than GBM. Unfortunately, its official installation document for R users on a Mac OS isn’t clear. In this post, I’m going to walk you through how to install the multi-thread version of the XGBoost R package on a Mac OS X El Capitan. You want the multi-thread version because you want to have the option of using more than 1 core of your machine simultaneously to run the algorithms in parallel.
Step 1. Open up your terminal and run the following cmd.
- install gcc-6.x.x with openmp. This can take a while (~ 30 minutes).
brew install gcc --without-multilib
- clone the repository.
git clone --recursive https://github.com/dmlc/xgboost
- build xgboost.
cd xgboost; cp make/config.mk ./config.mk; make -j4
- make an empty Makevars file and open it.
mkdir ~/.R touch ~/.R/Makevars open -a TextEdit ~/.R/Makevars
- paste the following into the Makevars file
CC = gcc-6 CXX = g++-6 CXX1X = g++-6 SHLIB_OPENMP_CFLAGS = -fopenmp SHLIB_OPENMP_CXXFLAGS = -fopenmp SHLIB_OPENMP_FCFLAGS = -fopenmp SHLIB_OPENMP_FFLAGS = -fopenmp
- save and close the file.
Step 2. Open Rstudio and install the xgboost package.
Done! Now you can start with some tutorials.