How to Install and Uninstall python-pomegranate-doc Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 21,2024

1. Install "python-pomegranate-doc" package

Please follow the guidelines below to install python-pomegranate-doc on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python-pomegranate-doc
            
                    
    
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2. Uninstall "python-pomegranate-doc" package

This guide covers the steps necessary to uninstall python-pomegranate-doc on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python-pomegranate-doc
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python-pomegranate-doc package on Ubuntu 21.10 (Impish Indri)

Package: python-pomegranate-doc
Architecture: all
Version: 0.13.5-1
Multi-Arch: foreign
Priority: optional
Section: universe/doc
Source: python-pomegranate
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Python Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 5381
Filename: pool/universe/p/python-pomegranate/python-pomegranate-doc_0.13.5-1_all.deb
Size: 5410908
MD5sum: 3915ce08aa2cc4cceea18d38e74e1716
SHA1: 784fab26226773721d0dfe587ceadbd27b562002
SHA256: 8a9ababe43baae5713c97217d3754bbc6629da6885a7b682c6f808f5879fbfdc
SHA512: b47af068e6e11a04587616d438642b61af244353e7c4943f262078212e4165ebec3381ae5bc752268cc8acfff812c49074e5334580a723ef7e9b3a133b59f39d
Homepage: https://github.com/jmschrei/pomegranate
Description-en: documentation accompanying probabilistic modelling library
pomegranate is a package for probabilistic models in Python that is
implemented in cython for speed. It's focus is on merging the easy-to-use
scikit-learn API with the modularity that comes with probabilistic
modeling to allow users to specify complicated models without needing to
worry about implementation details. The models are built from the ground
up with big data processing in mind and so natively support features
like out-of-core learning and parallelism.
.
This is the common documentation package.
Description-md5: 624b1b2e481885c2240a30615a9138ae