This book is written for version 0.15.1 of scikit-learn; use this version to ensure that the examples run correctly. If you have previously installed scikit-learn, you can retrieve the version number with the following code:
>>> import sklearn >>> sklearn.__version__ '0.15.1'
If you have not previously installed scikit-learn, you can install it from a package manager or build it from the source. We will review the installation processes for Linux, OS X, and Windows in the following sections, but refer to http://scikit-learn.org/stable/install.html for the latest instructions. The following instructions only assume that you have installed Python 2.6, Python 2.7, or Python 3.2 or newer. Go to http://www.python.org/download/ for instructions on how to install Python.
scikit-learn requires Setuptools, a third-party package that supports packaging and installing software for Python. Setuptools can be installed on Windows by running the bootstrap script at https://bitbucket.org/pypa/setuptools/raw/bootstrap/ez_setup.py.
Windows binaries for the 32- and 64-bit versions of scikit-learn are also available. If you cannot determine which version you need, install the 32-bit version. Both versions depend on NumPy 1.3 or newer. The 32-bit version of NumPy can be downloaded from http://sourceforge.net/projects/numpy/files/NumPy/. The 64-bit version can be downloaded from http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn.
A Windows installer for the 32-bit version of scikit-learn can be downloaded from http://sourceforge.net/projects/scikit-learn/files/. An installer for the 64-bit version of scikit-learn can be downloaded from http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn.
scikit-learn can also be built from the source code on Windows. Building requires a C/C++ compiler such as MinGW (http://www.mingw.org/), NumPy, SciPy, and Setuptools.
To build, clone the Git repository from https://github.com/scikit-learn/scikit-learn and execute the following command:
python setup.py install
There are several options to install scikit-learn on Linux, depending on your distribution. The preferred option to install scikit-learn on Linux is to use pip. You may also install it using a package manager, or build scikit-learn from its source.
To install scikit-learn using pip, execute the following command:
sudo pip install scikit-learn
To build scikit-learn, clone the Git repository from https://github.com/scikit-learn/scikit-learn. Then install the following dependencies:
sudo apt-get install python-dev python-numpy python-numpy-dev python-setuptools python-numpy-dev python-scipy libatlas-dev g++
Navigate to the repository's directory and execute the following command:
python setup.py install
scikit-learn can be installed on OS X using Macports:
sudo port install py26-sklearn
If Python 2.7 is installed, run the following command:
sudo port install py27-sklearn
scikit-learn can also be installed using pip with the following command:
pip install scikit-learn
To verify that scikit-learn has been installed correctly, open a Python console and execute the following:
>>> import sklearn >>> sklearn.__version__ '0.15.1'
To run scikit-learn's unit tests, first install the nose library. Then execute the following:
nosetest sklearn –exe
Congratulations! You've successfully installed scikit-learn.