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

Last updated: February 02,2025

1. Install "python-mlpy-doc" package

This guide covers the steps necessary to install python-mlpy-doc on Ubuntu 21.10 (Impish Indri)


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

In this section, we are going to explain the necessary steps to uninstall python-mlpy-doc on Ubuntu 21.10 (Impish Indri):


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

Package: python-mlpy-doc
Architecture: all
Version: 3.5.0+ds-1.2build2
Priority: optional
Section: universe/doc
Source: mlpy
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 3317
Depends: libjs-jquery, libjs-underscore
Suggests: python3-mlpy
Filename: pool/universe/m/mlpy/python-mlpy-doc_3.5.0+ds-1.2build2_all.deb
Size: 2694144
MD5sum: df7f459c6aade497cc2f00c7a859d20b
SHA1: e6ba70d9424daf3cc8ea74652e92f9dd0833aa5f
SHA256: 44fd9853851154799be3de07844a4cc4987f4ff37a28654b17d254a74112cf82
SHA512: 329638006a2c9bfd52900e7083df42d14dba6536ca5ecea27f953416d17a88183286d0542a96577261f19734f0c6423950b1284f1a5a282b1e74582ff601d0e0
Homepage: https://mlpy.fbk.eu/
Description-en: documentation and examples for mlpy
mlpy provides high level procedures that support, with few lines of
code, the design of rich Data Analysis Protocols (DAPs) for
preprocessing, clustering, predictive classification and feature
selection. Methods are available for feature weighting and ranking,
data resampling, error evaluation and experiment landscaping.
.
This package provides user documentation for mlpy in various formats
(HTML, PDF).
Description-md5: c37c5d40c22d603fd8b3f96a5dc3e60a