How to Install and Uninstall libalgorithm-svm-perl Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 13,2024

1. Install "libalgorithm-svm-perl" package

This guide covers the steps necessary to install libalgorithm-svm-perl on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libalgorithm-svm-perl
            
                    
    
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2. Uninstall "libalgorithm-svm-perl" package

This guide covers the steps necessary to uninstall libalgorithm-svm-perl on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                libalgorithm-svm-perl
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libalgorithm-svm-perl package on Ubuntu 20.10 (Groovy Gorilla)

Package: libalgorithm-svm-perl
Architecture: amd64
Version: 0.13-2build5
Priority: optional
Section: universe/perl
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Perl Group
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 106
Depends: perl (>= 5.30.0-9build1), perlapi-5.30.0, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libsvm3 (>= 3.21+ds)
Filename: pool/universe/liba/libalgorithm-svm-perl/libalgorithm-svm-perl_0.13-2build5_amd64.deb
Size: 29332
MD5sum: fb4bdbf6eced47c6bf079bb1aa73c9fb
SHA1: fd6dc767fb4b3e67001ab2bb8ae4778a94049e26
SHA256: d13d67868b3c98ef868e4a55afce2da81108ffb10132976a9ad32a1a06a65e15
SHA512: 4990ea3f69ed4606a24fa828184d91b96f5836f8379adab21c4d039b2eeed28e9eabd4a3418d228d36d7000ca177db60a8afd139dcd17e1f9893b7238d11a8dc
Homepage: https://metacpan.org/release/Algorithm-SVM
Description-en: bindings for the libsvm Support Vector Machine library
Algorithm::SVM implements a Support Vector Machine for Perl. Support Vector
Machines provide a method for creating classifcation functions from a set of
labeled training data, from which predictions can be made for subsequent data
sets.
Description-md5: 1ca6fbf200001c245865456b0f1b7a25