The recently introduced macos/arm64 platform (sometimes also known as Installing on Apple Silicon M1 hardware ¶ Minimum version of Scikit-learn dependencies are listed below along with itsįor installing on PyPy, PyP圓-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+Īre required. Matplotlib and some examples require scikit-image, pandas, or seaborn.

Scikit-learn plotting capabilities (i.e., functions start with “plot_”Īnd classes end with “Display”) require Matplotlib. Particular configurations of operating system and hardware (such as Linux on When using pip, please ensure that binary wheels are used,Īnd NumPy and SciPy are not recompiled from source, which can happen when using If you have not installed NumPy or SciPy yet, you can also install these usingĬonda or pip. Prior to running any Python command whenever you start a new terminal session. Note that you should always remember to activate the environment of your choice Package manager of the distribution (apt, dnf, pacman…). In particular under Linux is itĭiscouraged to install pip packages alongside the packages managed by the Version of scikit-learn with pip or conda and its dependencies independently ofĪny previously installed Python packages. Using such an isolated environment makes it possible to install a specific Strongly recommended to use a virtual environment (venv) or a conda environment. Note that in order to avoid potential conflicts with other packages it is

Python3 -m pip show scikit-learn # to see which version and where scikit-learn is installed python3 -m pip freeze # to see all packages installed in the active virtualenv python3 -c 'import sklearn sklearn.show_versions()' python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c 'import sklearn sklearn.show_versions()' python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c 'import sklearn sklearn.show_versions()' python -m pip show scikit-learn # to see which version and where scikit-learn is installed python -m pip freeze # to see all packages installed in the active virtualenv python -c 'import sklearn sklearn.show_versions()' conda list scikit-learn # to see which scikit-learn version is installed conda list # to see all packages installed in the active conda environment python -c 'import sklearn sklearn.show_versions()'

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