How to Install and Uninstall uARMSolver.x86_64 Package on CentOS Stream 9
Last updated: September 23,2024
1. Install "uARMSolver.x86_64" package
This is a short guide on how to install uARMSolver.x86_64 on CentOS Stream 9
$
sudo dnf update
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$
sudo dnf install
uARMSolver.x86_64
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2. Uninstall "uARMSolver.x86_64" package
This guide covers the steps necessary to uninstall uARMSolver.x86_64 on CentOS Stream 9:
$
sudo dnf remove
uARMSolver.x86_64
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$
sudo dnf autoremove
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3. Information about the uARMSolver.x86_64 package on CentOS Stream 9
Last metadata expiration check: 1:59:52 ago on Sat Mar 16 16:03:45 2024.
Available Packages
Name : uARMSolver
Version : 0.2.6
Release : 1.el9
Architecture : x86_64
Size : 488 k
Source : uARMSolver-0.2.6-1.el9.src.rpm
Repository : epel
Summary : Universal Association Rule Mining Solver
URL : https://github.com/firefly-cpp/uARMSolver
License : MIT
Description : uARMSolver allows users to preprocess their data in a transaction database, to
: make discretization of data, to search for association rules and to guide a
: presentation/visualization of the best rules found using external tools.
: Mining the association rules is defined as an optimization and solved using
: the nature-inspired algorithms that can be incorporated easily. Because
: the algorithms normally discover a huge amount of association rules, the
: framework enables a modular inclusion of so-called visual guiders for
: extracting the knowledge hidden in data, and visualize these using
: external tools.
Available Packages
Name : uARMSolver
Version : 0.2.6
Release : 1.el9
Architecture : x86_64
Size : 488 k
Source : uARMSolver-0.2.6-1.el9.src.rpm
Repository : epel
Summary : Universal Association Rule Mining Solver
URL : https://github.com/firefly-cpp/uARMSolver
License : MIT
Description : uARMSolver allows users to preprocess their data in a transaction database, to
: make discretization of data, to search for association rules and to guide a
: presentation/visualization of the best rules found using external tools.
: Mining the association rules is defined as an optimization and solved using
: the nature-inspired algorithms that can be incorporated easily. Because
: the algorithms normally discover a huge amount of association rules, the
: framework enables a modular inclusion of so-called visual guiders for
: extracting the knowledge hidden in data, and visualize these using
: external tools.