XGBoost Python Package
Project description
Notes
Windows users: pip installation may not work on some Windows environments, and it may cause unexpected errors.
Installation from pip on Windows is therefore currently disabled for further investigation; please install from Github instead.
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.
Requirements
Since this package contains C++ source code, pip needs a C++ compiler from the system to compile the source code on-the-fly.
macOS
On macOS, gcc@5 is required as later versions remove support for OpenMP. See here for more info.
Please install gcc@5 from Homebrew:
brew install gcc@5
After installing gcc@5, set it as your compiler:
export CC=gcc-5 export CXX=g++-5
Linux
Please install gcc:
sudo apt-get install build-essential # Ubuntu/Debian sudo yum groupinstall 'Development Tools' # CentOS/RHEL
Installation
From PyPI
For a stable version, install using pip:
pip install xgboost
From source
For an up-to-date version, install from Github:
Run ./build.sh in the root of the repo.
Make sure you have setuptools installed: pip install setuptools
Install with cd python-package; python setup.py install from the root of the repo
For Windows users, please use the Visual Studio project file under the Windows folder. See also the installation tutorial from Kaggle Otto Forum.
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'
Examples
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.
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