Installing scikit-learn

This book was written for version 0.18.1 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 by executing the following in a notebook or Python interpreter:

# In[1]:
import sklearn 
sklearn.__version__ 

# Out[1]:
'0.18.1'

The package is named sklearn because scikit-learn is not a valid Python package name.

If you have not previously installed scikit-learn, you may install it from a package manager or build it from source. We will review the installation processes for Ubuntu 16.04, Max OS, and Windows 10 in the following sections, but refer to http://scikit-learn.org/stable/install.html for the latest instructions. The following instructions assume only that you have installed Python >= 2.6 or Python >= 3.3. See http://www.python.org/download/ for instructions on installing Python.

Installing using pip

The easiest way to install scikit-learn is to use pip, the PyPA-recommended tool for installing Python packages. Install scikit-learn using pip as follows:

$ pip install -U scikit-learn

If pip is not available on your system, consult the following sections for installation instructions for various platforms.

Installing on Windows

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-bit 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.

Installing on Ubuntu 16.04

scikit-learn can be installed on Ubuntu 16.04 using apt.

$ sudo apt install python-scikits-learn

Installing on Mac OS

scikit-learn can be installed on OS X using Macports.

$ sudo port install py27-sklearn

Installing Anaconda

Anaconda is a free collection of more than 720 open source data science packages for Python including scikit-learn, NumPy, SciPy, pandas, and matplotlib. Anaconda is platform-agnostic and simple to install. See https://docs.continuum.io/anaconda/install/ for instructions for your operating system.

Verifying the installation

To verify that scikit-learn has been installed correctly, open a Python console and execute the following:

# In[1]:
import sklearn 
sklearn.__version__ 

# Out[1]:
'0.18.1'

To run scikit-learn's unit tests, first install the nose Python library. Then execute the following in a terminal emulator:

$ nosetest sklearn -exe  

Congratulations! You've successfully installed scikit-learn.