28 lines
1.8 KiB
Markdown
28 lines
1.8 KiB
Markdown
XGBoost Python Package
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======================
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Installation
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------------
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We are on [PyPI](https://pypi.python.org/pypi/xgboost) now. For stable version, please install using pip:
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* ```pip install xgboost```
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* 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 invesigation, please install from github.
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For up-to-date version, please install from github.
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* To make the python module, type ```./build.sh``` in the root directory of project
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* Make sure you have [setuptools](https://pypi.python.org/pypi/setuptools)
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* Install with `python setup.py install` from this directory.
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* For windows users, please use the Visual Studio project file under [windows folder](../windows/). See also the [installation tutorial](https://www.kaggle.com/c/otto-group-product-classification-challenge/forums/t/13043/run-xgboost-from-windows-and-python) from Kaggle Otto Forum.
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Examples
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------
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* Refer also to the walk through example in [demo folder](../demo/guide-python)
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* See also the [example scripts](../demo/kaggle-higgs) for Kaggle Higgs Challenge, including [speedtest script](../demo/kaggle-higgs/speedtest.py) on this dataset.
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Note
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-----
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* 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](http://brew.sh/) ```brew tap homebrew/versions; brew install gcc49```
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* 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/guide-python/sklearn_parallel.py) demo.
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