XGBoost Python Package
We are on PyPI now. For stable version, please install using pip:
pip install xgboost
- Since this package contains C++ source code,
pipneeds a C++ compiler from the system to compile the source code on-the-fly. Please follow the following instruction for each supported platform.
- Note for Mac OS X users: please install
brew tap homebrew/versions; brew install gcc --without-multilibfirstly.
- Note for Linux users: please install
sudo apt-get install build-essentialfirstly or using the corresponding package manager of the system.
- Note for windows users: this pip installation may not work on some windows environment, and it may cause unexpected errors. pip installation on windows is currently disabled for further investigation, please install from github.
For up-to-date version, please install from github.
To make the python module, type
./build.shin the root directory of project
Make sure you have setuptools
cd python-package; python setup.py installfrom this directory.
Add MinGW to the system PATH in Windows if you are using the latest version of xgboost which requires compilation:
`python import os os.environ['PATH'] = os.environ['PATH'] + ';C:\\Program Files\\mingw-w64\\x86_64-5.3.0-posix-seh-rt_v4-rev0\\mingw64\\bin' `
- Refer also to the walk through example in demo folder
- See also the example scripts for Kaggle Higgs Challenge, including speedtest script on this dataset.
- If you want to build xgboost on Mac OS X with multiprocessing support
where clang in XCode by default doesn't support, please install gcc
4.9 or higher using homebrew
brew tap homebrew/versions; brew install gcc --without-multilib
- If you want to run XGBoost process in parallel using the fork backend
for joblib/multiprocessing, you must build XGBoost without support
for OpenMP by
make no_omp=1. Otherwise, use the forkserver (in Python 3.4) or spawn backend. See the sklearn_parallel.py demo.