How to Install and Uninstall python3-mlpy-lib Package on Ubuntu 21.10 (Impish Indri)

Last updated: December 25,2024

1. Install "python3-mlpy-lib" package

This guide covers the steps necessary to install python3-mlpy-lib on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-mlpy-lib
            
                    
    
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2. Uninstall "python3-mlpy-lib" package

This tutorial shows how to uninstall python3-mlpy-lib on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python3-mlpy-lib
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-mlpy-lib package on Ubuntu 21.10 (Impish Indri)

Package: python3-mlpy-lib
Architecture: amd64
Version: 3.5.0+ds-1.2build2
Priority: optional
Section: universe/python
Source: mlpy
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1271
Provides: python3.9-mlpy-lib
Depends: libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgsl25 (>= 2.6), libstdc++6 (>= 5), python3 (<< 3.10), python3 (>= 3.9~), python3-numpy (>= 1:1.16.0~rc1), python3-numpy-abi9
Filename: pool/universe/m/mlpy/python3-mlpy-lib_3.5.0+ds-1.2build2_amd64.deb
Size: 319120
MD5sum: 78855479b92618f60cc773b4a15d88a8
SHA1: 1262283110c9ca79db947fb81993f7a6c760387a
SHA256: ed7d839a04d4bf73a65c7816039405aedb1f7888f526e9e52d7da17d6468489e
SHA512: 22012da68f59e062db3352d30bb19972bb0067eda2d374ed27155f70c05a78e77a2f76326c5db1432f2248def9527f83ebb599ddd122b9a14fbd1a183d310635
Homepage: https://mlpy.fbk.eu/
Description-en: low-level implementations and bindings 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 is an add-on package for the mlpy providing compiled core functionality.
Description-md5: ba9bef101432b8ed4e29cb0722f5ba89