I don't know about other people but I've had issue downloading conda/miniconda etc for a few hours now. For some reason it decided to install at /opt when using the graphical installer (i.e. I've been through the uninstall here How to uninstall Anaconda completely from macOS and additionall did an rm -rf /opt command. Seems that without this its not actually uninstalled (you. Download the installer: Miniconda installer for Windows. Anaconda installer for Windows. Verify your installer hashes. Double-click the.exe file. Follow the instructions on the screen. If you are unsure about any setting, accept the defaults. You can change them later. Updating conda ¶ Open your Anaconda Prompt from the start menu.
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- Anaconda is the birthplace of Python data science. We are a movement of data scientists, data-driven enterprises, and open source communities.
- Locate Anaconda. The first step you need to do is to locate the path of Anaconda. You will create a.
- 78636 total downloads Last upload: 2 months and 23 days ago Installers. Info: This package contains files in non-standard labels. Conda install linux-64 v0.2.1; win-32 v0.2.1; noarch v0.7.1; osx-64 v0.2.1; win-64 v0.2.1; To install this package with conda run one of the following: conda install -c conda.
There are different ways to install scikit-learn:
- Install the latest official release. Thisis the best approach for most users. It will provide a stable versionand pre-built packages are available for most platforms.
- Install the version of scikit-learn provided by youroperating system or Python distribution.This is a quick option for those who have operating systems or Pythondistributions that distribute scikit-learn.It might not provide the latest release version.
- Building the package from source. This is best for users who want thelatest-and-greatest features and aren’t afraid of runningbrand-new code. This is also needed for users who wish to contribute to theproject.
Installing the latest release¶
Operating SystemPackager
Install the 64bit version of Python 3, for instance from https://www.python.org.Install Python 3 using homebrew (
brew install python
) or by manually installing the package from https://www.python.org.Install python3 and python3-pip using the package manager of the Linux Distribution.Install conda (no administrator permission required).Then run:
In order to check your installation you can use
Note that in order to avoid potential conflicts with other packages it isstrongly recommended to use a virtual environment, e.g. python3
virtualenv
(see python3 virtualenv documentation) or conda environments.Using an isolated environment makes possible to install a specific version ofscikit-learn and its dependencies independently of any previously installedPython packages.In particular under Linux is it discouraged to install pip packages alongsidethe packages managed by the package manager of the distribution(apt, dnf, pacman…).
Note that you should always remember to activate the environment of your choiceprior to running any Python command whenever you start a new terminal session.
If you have not installed NumPy or SciPy yet, you can also install these usingconda or pip. When using pip, please ensure that binary wheels are used,and NumPy and SciPy are not recompiled from source, which can happen when usingparticular configurations of operating system and hardware (such as Linux ona Raspberry Pi).
If you must install scikit-learn and its dependencies with pip, you can installit as
scikit-learn[alldeps]
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Scikit-learn plotting capabilities (i.e., functions start with “plot_”and classes end with “Display”) require Matplotlib (>= 2.1.1). For running theexamples Matplotlib >= 2.1.1 is required. A few examples requirescikit-image >= 0.13, a few examples require pandas >= 0.18.0, some examplesrequire seaborn >= 0.9.0.
Warning
Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.Scikit-learn 0.21 supported Python 3.5-3.7.Scikit-learn 0.22 supported Python 3.5-3.8.Scikit-learn now requires Python 3.6 or newer.
Note
For installing on PyPy, PyPy3-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+are required.
Third party distributions of scikit-learn¶
Some third-party distributions provide versions ofscikit-learn integrated with their package-management systems.
These can make installation and upgrading much easier for users sincethe integration includes the ability to automatically installdependencies (numpy, scipy) that scikit-learn requires.
The following is an incomplete list of OS and python distributionsthat provide their own version of scikit-learn.
Arch Linux¶
Arch Linux’s package is provided through the official repositories as
python-scikit-learn
for Python.It can be installed by typing the following command:Debian/Ubuntu¶
The Debian/Ubuntu package is splitted in three different packages called
python3-sklearn
(python modules), python3-sklearn-lib
(low-levelimplementations and bindings), python3-sklearn-doc
(documentation).Only the Python 3 version is available in the Debian Buster (the more recentDebian distribution).Packages can be installed using apt-get
:Fedora¶
The Fedora package is called
python3-scikit-learn
for the python 3 version,the only one available in Fedora30.It can be installed using dnf
:NetBSD¶
scikit-learn is available via pkgsrc-wip:
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MacPorts for Mac OSX¶
The MacPorts package is named
py<XY>-scikits-learn
,where XY
denotes the Python version.It can be installed by typing the followingcommand:Canopy and Anaconda for all supported platforms¶
Canopy and Anaconda both ship a recentversion of scikit-learn, in addition to a large set of scientific pythonlibrary for Windows, Mac OSX and Linux.
Anaconda offers scikit-learn as part of its free distribution.
Intel conda channel¶
Intel maintains a dedicated conda channel that ships scikit-learn:
This version of scikit-learn comes with alternative solvers for some commonestimators. Those solvers come from the DAAL C++ library and are optimized formulti-core Intel CPUs.
Note that those solvers are not enabled by default, please refer to thedaal4py documentationfor more details.
Compatibility with the standard scikit-learn solvers is checked by running thefull scikit-learn test suite via automated continuous integration as reportedon https://github.com/IntelPython/daal4py.
WinPython for Windows¶
The WinPython project distributesscikit-learn as an additional plugin.
Troubleshooting¶
Error caused by file path length limit on Windows¶
It can happen that pip fails to install packages when reaching the default pathsize limit of Windows if Python is installed in a nested location such as the
AppData
folder structure under the user home directory, for instance:In this case it is possible to lift that limit in the Windows registry byusing the
regedit
tool:- Type “regedit” in the Windows start menu to launch
regedit
. - Go to the
ComputerHKEY_LOCAL_MACHINESYSTEMCurrentControlSetControlFileSystem
key. - Edit the value of the
LongPathsEnabled
property of that key and setit to 1. - Reinstall scikit-learn (ignoring the previous broken installation):
This post introduces how to install Miniconda on Mac.
(For installing Miniconda on Linux OS, check out this post.)
(For commonly used conda commands check this post.)
(For the comparison among Anaconda, Miniconda, and Virtualenv with pip, check this post.)
Step 1: download Miniconda (bash installer) from
see the highlighted in the pic below.
A file called Miniconda3-latest-MacOSX-x86_64.sh will be shown in your Downloads folder.
Step 2: Open a Terminalwindow.
(If you don’t know how to open a terminal window, through lauchpad type in Terminal, you will see the application.)
In the terminal window, type in
Step 3: run the bash “shell” script to install Miniconda
In the terminal window, type in the following.
Scroll through the license (press the Space bar or Enter to move through quickly), type ‘yes’ to approve the terms, and then accept all the installation defaults.
Step 4: Close the Terminal window, and open a new Terminal window.
in the newly opened Terminal window.
Type the following:
If you see something like the following, it means you have successfully installed conda via miniconda on your Mac.
conda 4.5.11
Step 5: Uninstalling Miniconda
To uninstall Python Anconda/Miniconda, we just simply remove the installation folder and remove the environment variables set in the hidden file .bash_profile in your home directory. For my installation, it will be just like this.
Then, you can edit the .bash_profile file and remove the following entries added for Anaconda/Miniconda directory from your PATH environment variable.
If you do not know where the hidden .bash_profile is located and how to edit it, see below for detailed instructions.
(1) Open a new terminal and go to your home directory. You can do this by using the command below.
(2) use the following command to list all files, including hidden files in your home directory.
(3) Use the
cat
command to see the contents of the hidden file .bash_profile. Type the following command into your terminal.You will see something like the following (depends on what you installed, if you installed Miniconda3, you will only see the first two lines. If you installed Anaconda3, you will see the bottom two lines.
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(4) To remove installed Miniconda/Anaconda from your .bash_profile use the command below to edit the file using the nano editor.
Remove the Miniconda /Anoconda path in your .bash_profile hidden file.
Then Type control + X to exit out of nano
Save changes by typing Y.
Close the terminal, and now Miniconda/Anaconda should be successfully uninstalled from your Mac.
(Tested on macOS Mojave. Note that you can install Miniconda onto your Mac even when you are not an admin user.)
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For commonly used conda commands check this post.
Mac Install Conda
For the comparison among Anaconda, Miniconda, and Virtualenv with pip, check this post.