How to Install and Uninstall elki-dev Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 10,2024

1. Install "elki-dev" package

This is a short guide on how to install elki-dev on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                elki-dev
            
                    
    
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2. Uninstall "elki-dev" package

Learn how to uninstall elki-dev on Ubuntu 20.10 (Groovy Gorilla):


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

Package: elki-dev
Architecture: all
Version: 0.7.1-10.1
Priority: extra
Section: universe/science
Source: elki
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Erich Schubert
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 29342
Depends: elki, default-jdk (>= 2:1.8)
Suggests: default-jdk-doc
Filename: pool/universe/e/elki/elki-dev_0.7.1-10.1_all.deb
Size: 24209936
MD5sum: 1dbb74e40207a8f0af4b6aecfd13dd1a
SHA1: d4bc7fcd467d63c52126507a7ed4c41ed8b68649
SHA256: b249413b01e9b9bcb362b663c8663cb5b01af0c94176cdefa269629bca922398
SHA512: d1b176bb0e005eae7eaf566c9812ee6339986eee95e18e3c14a03e041c5da13f6921f86c069d79c957ef009aac5bbb23c6577a2dd35b0a95a87f046aa1584a16
Homepage: https://elki-project.github.io/
Description-en: Data mining algorithm development framework - development files
ELKI: "Environment for Developing KDD-Applications Supported by
Index-Structures" is a development framework for data mining algorithms
written in Java. It includes a large variety of popular data mining
algorithms, distance functions and index structures.
.
Its focus is particularly on clustering and outlier detection methods, in
contrast to many other data mining toolkits that focus on classification.
Additionally, it includes support for index structures to improve algorithm
performance such as R*-Tree and M-Tree.
.
The modular architecture is meant to allow adding custom components such
as distance functions or algorithms, while being able to reuse the other
parts for evaluation.
.
This package contains the JavaDoc and the source code package.
Description-md5: 648c5c57de65de788810e6bbbd802f44