6f16f0ef58
* Fix various typos * Add override to functions that are overridden gcc gives warnings about functions that are being overridden by not being marked as oveirridden. This fixes it. * Use bst_float consistently Use bst_float for all the variables that involve weight, leaf value, gradient, hessian, gain, loss_chg, predictions, base_margin, feature values. In some cases, when due to additions and so on the value can take a larger value, double is used. This ensures that type conversions are minimal and reduces loss of precision.
68 lines
2.9 KiB
ReStructuredText
68 lines
2.9 KiB
ReStructuredText
XGBoost Python Package
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======================
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|PyPI version|
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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
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stable version, please install using pip:
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- ``pip install xgboost``
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- Since this package contains C++ source code, ``pip`` needs a C++ compiler from the system
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to compile the source code on-the-fly. Please follow the following instruction for each
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supported platform.
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- Note for Mac OS X users: please install ``gcc`` from ``brew`` by
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``brew tap homebrew/versions; brew install gcc --without-multilib`` firstly.
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- Note for Linux users: please install ``gcc`` by ``sudo apt-get install build-essential`` firstly
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or using the corresponding package manager of the system.
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- Note for windows users: this pip installation may not work on some
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windows environment, and it may cause unexpected errors. pip
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installation on windows is currently disabled for further
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investigation, 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
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of project
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- Make sure you have
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`setuptools <https://pypi.python.org/pypi/setuptools>`__
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- Install with ``cd python-package; python setup.py install`` from this directory.
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- For windows users, please use the Visual Studio project file under
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`windows folder <../windows/>`__. See also the `installation
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tutorial <https://www.kaggle.com/c/otto-group-product-classification-challenge/forums/t/13043/run-xgboost-from-windows-and-python>`__
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from Kaggle Otto Forum.
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- Add MinGW to the system PATH in Windows if you are using the latest version of xgboost which requires compilation:
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```python
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import os
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os.environ['PATH'] = os.environ['PATH'] + ';C:\\Program Files\\mingw-w64\\x86_64-5.3.0-posix-seh-rt_v4-rev0\\mingw64\\bin'
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```
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Examples
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--------
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- Refer also to the walk through example in `demo
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folder <https://github.com/dmlc/xgboost/tree/master/demo/guide-python>`__
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- See also the `example scripts <https://github.com/dmlc/xgboost/tree/master/demo/kaggle-higgs>`__ for Kaggle
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Higgs Challenge, including `speedtest
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script <https://github.com/dmlc/xgboost/tree/master/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
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where clang in XCode by default doesn't support, please install gcc
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4.9 or higher using `homebrew <http://brew.sh/>`__
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``brew tap homebrew/versions; brew install gcc --without-multilib``
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- If you want to run XGBoost process in parallel using the fork backend
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for joblib/multiprocessing, you must build XGBoost without support
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for OpenMP by ``make no_omp=1``. Otherwise, use the forkserver (in
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Python 3.4) or spawn backend. See the
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`sklearn\_parallel.py <../demo/guide-python/sklearn_parallel.py>`__
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demo.
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.. |PyPI version| image:: https://badge.fury.io/py/xgboost.svg
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:target: http://badge.fury.io/py/xgboost
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