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

Last updated: November 22,2024

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

In this section, we are going to explain the necessary steps to install libghc-hierarchical-clustering-prof on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libghc-hierarchical-clustering-prof
            
                    
    
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2. Uninstall "libghc-hierarchical-clustering-prof" package

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


    
        
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                sudo apt remove
            
                        
                libghc-hierarchical-clustering-prof
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: libghc-hierarchical-clustering-prof
Source: haskell-hierarchical-clustering (0.4.7-3)
Version: 0.4.7-3+b1
Installed-Size: 546
Maintainer: Debian Haskell Group
Architecture: amd64
Provides: libghc-hierarchical-clustering-prof-0.4.7-9e5ca
Depends: libghc-array-prof-0.5.4.0-0952c, libghc-base-prof-4.17.2.0-68dfe, libghc-containers-prof-0.6.7-a1650, libghc-hierarchical-clustering-dev (= 0.4.7-3+b1)
Size: 75000
SHA256: adb4c09aa03a7e0a9f7925a72ddec0d0f743e3ea5478be457c3b48c87d9c916b
SHA1: 6ac83953fdecc0c256e0ab224a22c52556a5d2f2
MD5sum: 7d8f37e00b5fa8fe979db98845c37e34
Description: fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries
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, compiled
for profiling. See http://www.haskell.org/ for more information on Haskell.
Description-md5:
Homepage: https://hackage.haskell.org/package/hierarchical-clustering
Section: haskell
Priority: optional
Filename: pool/main/h/haskell-hierarchical-clustering/libghc-hierarchical-clustering-prof_0.4.7-3+b1_amd64.deb