Fixed issue #5830, capitalization in advanced installation documenation
This commit is contained in:
Scott Andrews
Andreas Mueller
parent
c726085e20
commit
f241f5f14e
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@ -52,31 +52,31 @@ Linux
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-----
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At this time scikit-learn does not provide official binary packages for Linux
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so you have to build from source if you want the lastest version.
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so you have to build from source if you want the latest version.
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If you don't need the newest version, consider using your package manager to
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install scikit-learn. it is usually the easiest way, but might not provide the
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install scikit-learn. It is usually the easiest way, but might not provide the
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newest version.
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installing build dependencies
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Installing build dependencies
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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installing from source requires you to have installed the scikit-learn runtime
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dependencies, python development headers and a working C/C++ compiler.
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under debian-based operating systems, which include ubuntu, if you have
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python 2 you can install all these requirements by issuing::
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Installing from source requires you to have installed the scikit-learn runtime
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dependencies, Python development headers and a working C/C++ compiler.
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Under Debian-based operating systems, which include Ubuntu, if you have
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Python 2 you can install all these requirements by issuing::
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sudo apt-get install build-essential python-dev python-setuptools \
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python-numpy python-scipy \
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libatlas-dev libatlas3gf-base
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if you have python 3::
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If you have Python 3::
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sudo apt-get install build-essential python3-dev python3-setuptools \
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python3-numpy python3-scipy \
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libatlas-dev libatlas3gf-base
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on recent debian and ubuntu (e.g. ubuntu 13.04 or later) make sure that atlas
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is used to provide the implementation of the blas and lapack linear algebra
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On recent Debian and Ubuntu (e.g. Ubuntu 13.04 or later) make sure that ATLAS
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is used to provide the implementation of the BLAS and LAPACK linear algebra
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routines::
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sudo update-alternatives --set libblas.so.3 \
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@ -86,24 +86,24 @@ routines::
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.. note::
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in order to build the documentation and run the example code contains in
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In order to build the documentation and run the example code contains in
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this documentation you will need matplotlib::
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sudo apt-get install python-matplotlib
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.. note::
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the above installs the atlas implementation of blas
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(the basic linear algebra subprograms library).
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ubuntu 11.10 and later, and recent (testing) versions of debian,
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offer an alternative implementation called openblas.
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The above installs the ATLAS implementation of BLAS
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(the Basic Linear Algebra Subprograms library).
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Ubuntu 11.10 and later, and recent (testing) versions of Debian,
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offer an alternative implementation called OpenBLAS.
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using openblas can give speedups in some scikit-learn modules,
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but can freeze joblib/multiprocessing prior to openblas version 0.2.8-4,
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Using OpenBLAS can give speedups in some scikit-learn modules,
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but can freeze joblib/multiprocessing prior to OpenBLAS version 0.2.8-4,
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so using it is not recommended unless you know what you're doing.
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if you do want to use openblas, then replacing atlas only requires a couple
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of commands. atlas has to be removed, otherwise numpy may not work::
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If you do want to use OpenBLAS, then replacing ATLAS only requires a couple
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of commands. ATLAS has to be removed, otherwise NumPy may not work::
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sudo apt-get remove libatlas3gf-base libatlas-dev
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sudo apt-get install libopenblas-dev
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@ -113,30 +113,30 @@ routines::
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sudo update-alternatives --set liblapack.so.3 \
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/usr/lib/lapack/liblapack.so.3
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on red hat and clones (e.g. centos), install the dependencies using::
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On Red Hat and clones (e.g. CentOS), install the dependencies using::
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sudo yum -y install gcc gcc-c++ numpy python-devel scipy
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building scikit-learn with pip
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Building scikit-learn with pip
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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this is usually the fastest way to install or upgrade to the latest stable
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This is usually the fastest way to install or upgrade to the latest stable
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release::
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pip install --user --install-option="--prefix=" -u scikit-learn
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pip install --user --install-option="--prefix=" -U scikit-learn
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the ``--user`` flag asks pip to install scikit-learn in the ``$home/.local``
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folder therefore not requiring root permission. this flag should make pip
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The ``--user`` flag asks pip to install scikit-learn in the ``$HOME/.local``
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folder therefore not requiring root permission. This flag should make pip
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ignore any old version of scikit-learn previously installed on the system while
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benefiting from system packages for numpy and scipy. those dependencies can
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benefiting from system packages for numpy and scipy. Those dependencies can
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be long and complex to build correctly from source.
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the ``--install-option="--prefix="`` flag is only required if python has a
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The ``--install-option="--prefix="`` flag is only required if Python has a
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``distutils.cfg`` configuration with a predefined ``prefix=`` entry.
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from source package
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From source package
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~~~~~~~~~~~~~~~~~~~
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download the source package from
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@ -144,7 +144,7 @@ download the source package from
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cd into the source directory.
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This packages uses distutils, which is the default way of installing
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python modules. the install command is::
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python modules. The install command is::
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python setup.py install
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@ -154,27 +154,27 @@ or alternatively (also from within the scikit-learn source folder)::
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.. warning::
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packages installed with the ``python setup.py install`` command cannot
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be uninstalled nor upgraded by ``pip`` later. to properly uninstall
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Packages installed with the ``python setup.py install`` command cannot
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be uninstalled nor upgraded by ``pip`` later. To properly uninstall
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scikit-learn in that case it is necessary to delete the ``sklearn`` folder
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from your python ``site-packages`` directory.
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from your Python ``site-packages`` directory.
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windows
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Windows
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-------
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first, you need to install `numpy <http://www.numpy.org/>`_ and `scipy
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First, you need to install `numpy <http://www.numpy.org/>`_ and `scipy
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<http://www.scipy.org/>`_ from their own official installers.
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wheel packages (.whl files) for scikit-learn from `pypi
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Wheel packages (.whl files) for scikit-learn from `pypi
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<https://pypi.python.org/pypi/scikit-learn/>`_ can be installed with the `pip
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<https://pip.readthedocs.io/en/stable/installing/>`_ utility.
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open a console and type the following to install or upgrade scikit-learn to the
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Open a console and type the following to install or upgrade scikit-learn to the
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latest stable release::
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pip install -u scikit-learn
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pip install -U scikit-learn
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if there are no binary packages matching your python, version you might
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If there are no binary packages matching your python, version you might
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to try to install scikit-learn and its dependencies from `christoph gohlke
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unofficial windows installers
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<http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn>`_
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@ -186,23 +186,23 @@ or from a :ref:`python distribution <install_by_distribution>` instead.
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Third party distributions of scikit-learn
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=========================================
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some third-party distributions are now providing versions of
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Some third-party distributions are now providing versions of
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scikit-learn integrated with their package-management systems.
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these can make installation and upgrading much easier for users since
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These can make installation and upgrading much easier for users since
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the integration includes the ability to automatically install
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dependencies (numpy, scipy) that scikit-learn requires.
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the following is an incomplete list of python and os distributions
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The following is an incomplete list of python and os distributions
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that provide their own version of scikit-learn.
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macports for mac osx
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MacPorts for Mac OSX
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--------------------
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the macports package is named ``py<xy>-scikits-learn``,
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where ``xy`` denotes the python version.
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it can be installed by typing the following
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The MacPorts package is named ``py<XY>-scikits-learn``,
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where ``XY`` denotes the Python version.
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It can be installed by typing the following
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command::
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sudo port install py26-scikit-learn
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@ -212,39 +212,39 @@ or::
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sudo port install py27-scikit-learn
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arch linux
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Arch Linux
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----------
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arch linux's package is provided through the `official repositories
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Arch Linux's package is provided through the `official repositories
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<https://www.archlinux.org/packages/?q=scikit-learn>`_ as
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``python-scikit-learn`` for python 3 and ``python2-scikit-learn`` for python 2.
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it can be installed by typing the following command:
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``python-scikit-learn`` for Python 3 and ``python2-scikit-learn`` for Python 2.
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It can be installed by typing the following command:
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.. code-block:: none
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# pacman -s python-scikit-learn
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# pacman -S python-scikit-learn
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or:
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.. code-block:: none
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# pacman -s python2-scikit-learn
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# pacman -S python2-scikit-learn
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depending on the version of python you use.
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depending on the version of Python you use.
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netbsd
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NetBSD
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------
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scikit-learn is available via `pkgsrc-wip <http://pkgsrc-wip.sourceforge.net/>`_:
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http://pkgsrc.se/wip/py-scikit_learn
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fedora
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Fedora
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------
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the fedora package is called ``python-scikit-learn`` for the python 2 version
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and ``python3-scikit-learn`` for the python 3 version. both versions can
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The Fedora package is called ``python-scikit-learn`` for the Python 2 version
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and ``python3-scikit-learn`` for the Python 3 version. Both versions can
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be installed using ``yum``::
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$ sudo yum install python-scikit-learn
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@ -254,103 +254,103 @@ or::
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$ sudo yum install python3-scikit-learn
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building on windows
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Building on windows
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-------------------
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to build scikit-learn on windows you need a working C/C++ compiler in
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To build scikit-learn on Windows you need a working C/C++ compiler in
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addition to numpy, scipy and setuptools.
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picking the right compiler depends on the version of python (2 or 3)
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and the architecture of the python interpreter, 32-bit or 64-bit.
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you can check the python version by running the following in ``cmd`` or
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Picking the right compiler depends on the version of Python (2 or 3)
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and the architecture of the Python interpreter, 32-bit or 64-bit.
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You can check the Python version by running the following in ``cmd`` or
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``powershell`` console::
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python --version
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and the architecture with::
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python -c "import struct; print(struct.calcsize('p') * 8)"
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python -c "import struct; print(struct.calcsize('P') * 8)"
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the above commands assume that you have the python installation folder in your
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path environment variable.
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The above commands assume that you have the Python installation folder in your
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PATH environment variable.
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32-bit python
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32-bit Python
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-------------
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for 32-bit python it is possible use the standalone installers for
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For 32-bit python it is possible use the standalone installers for
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`microsoft visual c++ express 2008 <http://download.microsoft.com/download/A/5/4/A54BADB6-9C3F-478D-8657-93B3FC9FE62D/vcsetup.exe>`_
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for python 2 or microsoft visual c++ express 2010 for python 3.
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for Python 2 or Microsoft Visual C++ Express 2010 for Python 3.
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once installed you should be able to build scikit-learn without any
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Once installed you should be able to build scikit-learn without any
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particular configuration by running the following command in the scikit-learn
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folder::
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python setup.py install
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64-bit python
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64-bit Python
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-------------
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for the 64-bit architecture, you either need the full visual studio or
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the free windows sdks that can be downloaded from the links below.
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For the 64-bit architecture, you either need the full Visual Studio or
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the free Windows SDKs that can be downloaded from the links below.
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the windows sdks include the msvc compilers both for 32 and 64-bit
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architectures. they come as a ``grmsdkx_en_dvd.iso`` file that can be mounted
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The Windows SDKs include the MSVC compilers both for 32 and 64-bit
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architectures. They come as a ``GRMSDKX_EN_DVD.iso`` file that can be mounted
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as a new drive with a ``setup.exe`` installer in it.
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- for python 2 you need sdk **v7.0**: `ms windows sdk for windows 7 and .net
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framework 3.5 sp1
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- For Python 2 you need SDK **v7.0**: `MS Windows SDK for Windows 7 and .NET
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Framework 3.5 SP1
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<https://www.microsoft.com/en-us/download/details.aspx?id=18950>`_
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- for python 3 you need sdk **v7.1**: `ms windows sdk for windows 7 and .net
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framework 4
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- For Python 3 you need SDK **v7.1**: `MS Windows SDK for Windows 7 and .NET
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Framework 4
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<https://www.microsoft.com/en-us/download/details.aspx?id=8442>`_
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both sdks can be installed in parallel on the same host. to use the windows
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sdks, you need to setup the environment of a ``cmd`` console launched with the
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following flags (at least for sdk v7.0)::
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Both SDKs can be installed in parallel on the same host. To use the Windows
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SDKs, you need to setup the environment of a ``cmd`` console launched with the
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following flags (at least for SDK v7.0)::
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cmd /e:on /v:on /k
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cmd /E:ON /V:ON /K
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then configure the build environment with::
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Then configure the build environment with::
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set distutils_use_sdk=1
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set mssdk=1
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"c:\program files\microsoft sdks\windows\v7.0\setup\windowssdkver.exe" -q -version:v7.0
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"c:\program files\microsoft sdks\windows\v7.0\bin\setenv.cmd" /x64 /release
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SET DISTUTILS_USE_SDK=1
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SET MSSdk=1
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"C:\Program Files\Microsoft SDKs\Windows\v7.0\Setup\WindowsSdkVer.exe" -q -version:v7.0
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"C:\Program Files\Microsoft SDKs\Windows\v7.0\Bin\SetEnv.cmd" /x64 /release
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finally you can build scikit-learn in the same ``cmd`` console::
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Finally you can build scikit-learn in the same ``cmd`` console::
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python setup.py install
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replace ``v7.0`` by the ``v7.1`` in the above commands to do the same for
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python 3 instead of python 2.
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Replace ``v7.0`` by the ``v7.1`` in the above commands to do the same for
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Python 3 instead of Python 2.
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replace ``/x64`` by ``/x86`` to build for 32-bit python instead of 64-bit
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python.
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Replace ``/x64`` by ``/x86`` to build for 32-bit Python instead of 64-bit
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Python.
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building binary packages and installers
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Building binary packages and installers
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---------------------------------------
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the ``.whl`` package and ``.exe`` installers can be built with::
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The ``.whl`` package and ``.exe`` installers can be built with::
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pip install wheel
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python setup.py bdist_wheel bdist_wininst -b doc/logos/scikit-learn-logo.bmp
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the resulting packages are generated in the ``dist/`` folder.
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The resulting packages are generated in the ``dist/`` folder.
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using an alternative compiler
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Using an alternative compiler
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-----------------------------
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it is possible to use `mingw <http://www.mingw.org>`_ (a port of gcc to windows
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os) as an alternative to msvc for 32-bit python. not that extensions built with
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mingw32 can be redistributed as reusable packages as they depend on gcc runtime
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It is possible to use `MinGW <http://www.mingw.org>`_ (a port of GCC to Windows
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OS) as an alternative to MSVC for 32-bit Python. Not that extensions built with
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mingw32 can be redistributed as reusable packages as they depend on GCC runtime
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libraries typically not installed on end-users environment.
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to force the use of a particular compiler, pass the ``--compiler`` flag to the
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To force the use of a particular compiler, pass the ``--compiler`` flag to the
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build step::
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python setup.py build --compiler=my_compiler install
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@ -360,62 +360,62 @@ where ``my_compiler`` should be one of ``mingw32`` or ``msvc``.
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.. _install_bleeding_edge:
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bleeding edge
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Bleeding Edge
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=============
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see section :ref:`git_repo` on how to get the development version. then follow
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See section :ref:`git_repo` on how to get the development version. Then follow
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the previous instructions to build from source depending on your platform.
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You will also require Cython >=0.23 in order to build the development version.
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.. _testing:
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testing
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Testing
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=======
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testing scikit-learn once installed
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Testing scikit-learn once installed
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-----------------------------------
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testing requires having the `nose
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<https://nose.readthedocs.io/en/latest/>`_ library. after
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Testing requires having the `nose
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<https://somethingaboutorange.com/mrl/projects/nose/>`_ library. After
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installation, the package can be tested by executing *from outside* the
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source directory::
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$ nosetests -v sklearn
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under windows, it is recommended to use the following command (adjust the path
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Under Windows, it is recommended to use the following command (adjust the path
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to the ``python.exe`` program) as using the ``nosetests.exe`` program can badly
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interact with tests that use ``multiprocessing``::
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c:\python34\python.exe -c "import nose; nose.main()" -v sklearn
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C:\Python34\python.exe -c "import nose; nose.main()" -v sklearn
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this should give you a lot of output (and some warnings) but
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This should give you a lot of output (and some warnings) but
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eventually should finish with a message similar to::
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ran 3246 tests in 260.618s
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ok (skip=20)
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Ran 3246 tests in 260.618s
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OK (SKIP=20)
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otherwise, please consider posting an issue into the `bug tracker
|
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Otherwise, please consider posting an issue into the `bug tracker
|
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<https://github.com/scikit-learn/scikit-learn/issues>`_ or to the
|
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:ref:`mailing_lists` including the traceback of the individual failures
|
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and errors. please include your operation system, your version of numpy, scipy
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and errors. Please include your operating system, your version of NumPy, SciPy
|
||||
and scikit-learn, and how you installed scikit-learn.
|
||||
|
||||
|
||||
testing scikit-learn from within the source folder
|
||||
Testing scikit-learn from within the source folder
|
||||
--------------------------------------------------
|
||||
|
||||
scikit-learn can also be tested without having the package
|
||||
installed. for this you must compile the sources inplace from the
|
||||
Scikit-learn can also be tested without having the package
|
||||
installed. For this you must compile the sources inplace from the
|
||||
source directory::
|
||||
|
||||
python setup.py build_ext --inplace
|
||||
|
||||
test can now be run using nosetests::
|
||||
Test can now be run using nosetests::
|
||||
|
||||
nosetests -v sklearn/
|
||||
|
||||
this is automated by the commands::
|
||||
This is automated by the commands::
|
||||
|
||||
make in
|
||||
|
||||
|
|
@ -424,7 +424,7 @@ and::
|
|||
make test
|
||||
|
||||
|
||||
you can also install a symlink named ``site-packages/scikit-learn.egg-link``
|
||||
You can also install a symlink named ``site-packages/scikit-learn.egg-link``
|
||||
to the development folder of scikit-learn with::
|
||||
|
||||
pip install --editable .
|
||||
|
|
|
|||
Loading…
Reference in New Issue