How to Install and Uninstall libghc-hierarchical-clustering-dev Package on Kali Linux

Last updated: May 09,2024

1. Install "libghc-hierarchical-clustering-dev" package

Please follow the guidance below to install libghc-hierarchical-clustering-dev on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libghc-hierarchical-clustering-dev
            
                    
    
    Copied

2. Uninstall "libghc-hierarchical-clustering-dev" package

Here is a brief guide to show you how to uninstall libghc-hierarchical-clustering-dev on Kali Linux:


    
        
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                sudo apt remove
            
                        
                libghc-hierarchical-clustering-dev
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libghc-hierarchical-clustering-dev package on Kali Linux

Package: libghc-hierarchical-clustering-dev
Source: haskell-hierarchical-clustering (0.4.7-3)
Version: 0.4.7-3+b1
Installed-Size: 609
Maintainer: Debian Haskell Group
Architecture: amd64
Provides: libghc-hierarchical-clustering-dev-0.4.7-9e5ca
Depends: libghc-array-dev-0.5.4.0-0952c, libghc-base-dev-4.17.2.0-68dfe, libghc-containers-dev-0.6.7-a1650, libc6 (>= 2.2.5), libgmp10 (>= 2:6.3.0+dfsg)
Size: 86224
SHA256: ec4db66f39e49e9412172ff294a044d8200013438d970479b5446e47655e4818
SHA1: 5b84bcf2743ca2ab8ab4c8418b6d6031f8b283cf
MD5sum: dc195a6ce49189a0049b9512f31f1bd2
Description: fast algorithms for single, average/UPGMA and complete linkage clustering
This package provides a function to create a dendrogram from a
list of items and a distance function between them. Initially
a singleton cluster is created for each item, and then new,
bigger clusters are created by merging the two clusters with
least distance between them. The distance between two clusters
is calculated according to the linkage type. The dendrogram
represents not only the clusters but also the order on which
they were created.
.
This package has many implementations with different
performance characteristics. There are SLINK and CLINK
algorithm implementations that are optimal in both space and
time. There are also naive implementations using a distance
matrix. Using the dendrogram function from
Data.Clustering.Hierarchical automatically chooses the best
implementation we have.
.
This package provides a library for the Haskell programming language.
See http://www.haskell.org/ for more information on Haskell.
Description-md5:
Homepage: https://hackage.haskell.org/package/hierarchical-clustering
Ghc-Package: hierarchical-clustering-0.4.7-6K3QkxvfntGG4eYoqmp0Bn
Section: haskell
Priority: optional
Filename: pool/main/h/haskell-hierarchical-clustering/libghc-hierarchical-clustering-dev_0.4.7-3+b1_amd64.deb