Below is the guide to install XGBoost Python module on Windows system (64bit). It can be used as another ML model in Scikit-Learn. For more information on XGBoost or “Extreme Gradient Boosting”, you can refer to the following material.
The following steps are compiled based on combined information from below 3 links:
Resources to be used as below. All have to be for 64bit platform.
- Git bash for windows
- Mingwin (TDM-GCC) for building. Need to ensure OpenMP install option is ticked. Please see details here.
Below commands have to be performed on the Git Bash on Windows. (may encounter error if using windows cmd prompt)
- git clone –recursive https://github.com/dmlc/xgboost
- cd xgboost
- git submodule init
- git submodule update
Additional steps below to resolve the “build” issue based on information
- cd dmlc-core
- mingw32-make -j4
- cd ../rabit
- mingw32-make lib/librabit_empty.a -j4
- cd ..
- cp make/mingw64.mk config.mk
- mingw32-make -j4
You can use an alias for mingw32-make. (alias make=’mingw32-make’)
Finally, setup for python installation.
- cd xgboost\python-package
- python setup.py install
Note that python, numpy and scipy need to be installed to use. All have to be on 64 bit platform.
After successful installation, you can try out the following quick example to verify that the xgboost module is working.
Simply Python 