How to Install and Uninstall python3-pyfim.x86_64 Package on Fedora 39
Last updated: November 28,2024
1. Install "python3-pyfim.x86_64" package
Please follow the instructions below to install python3-pyfim.x86_64 on Fedora 39
$
sudo dnf update
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$
sudo dnf install
python3-pyfim.x86_64
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2. Uninstall "python3-pyfim.x86_64" package
This guide let you learn how to uninstall python3-pyfim.x86_64 on Fedora 39:
$
sudo dnf remove
python3-pyfim.x86_64
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$
sudo dnf autoremove
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3. Information about the python3-pyfim.x86_64 package on Fedora 39
Last metadata expiration check: 4:10:22 ago on Thu Mar 7 17:44:52 2024.
Available Packages
Name : python3-pyfim
Version : 6.28
Release : 14.fc39
Architecture : x86_64
Size : 183 k
Source : python-pyfim-6.28-14.fc39.src.rpm
Repository : fedora
Summary : Frequent Item Set Mining and Association Rule Induction
URL : http://www.borgelt.net/pyfim.html
License : MIT
Description :
: PyFIM is an extension module that makes several frequent item set mining
: implementations available as functions in Python 2.7.x & 3.5.x. Currently
: apriori, eclat, fpgrowth, sam, relim, carpenter, ista, accretion and apriacc
: are available as functions, although the interfaces do not offer all of the
: options of the command line program. (Note that lcm is available as an
: algorithm mode of eclat.) There is also a "generic" function fim, which is
: essentially the same function as fpgrowth, only with a simplified interface
: (fewer options). Finally, there is a function arules for generating association
: rules (simplified interface compared to apriori, eclat and fpgrowth, which can
: also be used to generate association rules.
:
: How to use the functions can be seen in the example scripts testfim.py and
: testacc.py in the source package (directory pyfim/ex). From a Python script or
: command prompt interface, call help(fim), help(apriori) (or help(fim.apriori)),
: help(eclat) (or help(fim.eclat)) etc. or print, for example, apriori.__doc__,
: eclat.__doc__ etc. for a description of the functions and their arguments.
:
: This extension module was originally developed for Python 2.7. The shared
: objects made available above were compiled particularly for Python 2.7.11 and
: Python 3.5.1 on Ubuntu 16.04 LTS and the dynamic modules made available above
: were compiled for Python 2.7.10 and Python 3.5.1 on Windows 10.
Available Packages
Name : python3-pyfim
Version : 6.28
Release : 14.fc39
Architecture : x86_64
Size : 183 k
Source : python-pyfim-6.28-14.fc39.src.rpm
Repository : fedora
Summary : Frequent Item Set Mining and Association Rule Induction
URL : http://www.borgelt.net/pyfim.html
License : MIT
Description :
: PyFIM is an extension module that makes several frequent item set mining
: implementations available as functions in Python 2.7.x & 3.5.x. Currently
: apriori, eclat, fpgrowth, sam, relim, carpenter, ista, accretion and apriacc
: are available as functions, although the interfaces do not offer all of the
: options of the command line program. (Note that lcm is available as an
: algorithm mode of eclat.) There is also a "generic" function fim, which is
: essentially the same function as fpgrowth, only with a simplified interface
: (fewer options). Finally, there is a function arules for generating association
: rules (simplified interface compared to apriori, eclat and fpgrowth, which can
: also be used to generate association rules.
:
: How to use the functions can be seen in the example scripts testfim.py and
: testacc.py in the source package (directory pyfim/ex). From a Python script or
: command prompt interface, call help(fim), help(apriori) (or help(fim.apriori)),
: help(eclat) (or help(fim.eclat)) etc. or print, for example, apriori.__doc__,
: eclat.__doc__ etc. for a description of the functions and their arguments.
:
: This extension module was originally developed for Python 2.7. The shared
: objects made available above were compiled particularly for Python 2.7.11 and
: Python 3.5.1 on Ubuntu 16.04 LTS and the dynamic modules made available above
: were compiled for Python 2.7.10 and Python 3.5.1 on Windows 10.