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

Last updated: May 20,2024

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

This tutorial shows how to install libghc-hierarchical-clustering-doc on Kali Linux


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

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

This is a short guide on how to uninstall libghc-hierarchical-clustering-doc on Kali Linux:


    
        
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                sudo apt remove
            
                        
                libghc-hierarchical-clustering-doc
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: libghc-hierarchical-clustering-doc
Source: haskell-hierarchical-clustering
Version: 0.4.7-3
Installed-Size: 690
Maintainer: Debian Haskell Group
Architecture: all
Depends: haddock-interface-41
Recommends: ghc-doc, libghc-hierarchical-clustering-dev, libjs-mathjax
Suggests: libghc-hierarchical-clustering-prof
Size: 64648
SHA256: 78f382b723d655b0ead18ed74dd6926fc67a3be3e4069c707fd58812001a8f80
SHA1: 5c9f3b62597993baf54b9019c3bd91aa1dcfe46d
MD5sum: eb721f7482fee7a15e4da81d26e2d04f
Description: fast algorithms for single, average/UPGMA and complete linkage clustering; documentation
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 the documentation for 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
Section: doc
Priority: optional
Filename: pool/main/h/haskell-hierarchical-clustering/libghc-hierarchical-clustering-doc_0.4.7-3_all.deb