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ajsrk / packages / xgboost 0.83.dev0

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  • Last upload: 7 years and 4 days ago

Installers

pip install

To install this package run one of the following:
pip install -i https://pypi.anaconda.org/ajsrk/simple xgboost

Description

This xgboost version has multi-gpu support and is compiled with nvcc -2.4.2 and CUDA - 9.2. Please make sure you have installed CUDA-9.2 and NVCC-2.4.2 before installing this package.

====================== XGBoost Python Package ======================

    |PyPI version|

    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 <https://xgboost.readthedocs.io/en/latest/build.html>`_ 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/guide-python/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 <https://github.com/dmlc/xgboost/issues/1501#issuecomment-292209578>`_ for more info.

    Please install ``gcc@5`` from `Homebrew <https://brew.sh/>`_::

        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 <https://pypi.python.org/pypi/xgboost>`_
    ---------------------------------------------------

    For a stable version, install using ``pip``::

        pip install xgboost

    From source
    -----------

    For an up-to-date version, `install from Github <https://xgboost.readthedocs.io/en/latest/build.html>`_:

    -  Run ``./build.sh`` in the root of the repo.
    -  Make sure you have `setuptools <https://pypi.python.org/pypi/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 <../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.
    -  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 <https://github.com/dmlc/xgboost/tree/master/demo/guide-python>`_.
    -  See also the `example scripts <https://github.com/dmlc/xgboost/tree/master/demo/kaggle-higgs>`_ for Kaggle
       Higgs Challenge, including `speedtest script <https://github.com/dmlc/xgboost/tree/master/demo/kaggle-higgs/speedtest.py>`_ on this dataset.

    .. |PyPI version| image:: https://badge.fury.io/py/xgboost.svg
       :target: http://badge.fury.io/py/xgboost

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