How to Install and Uninstall r-cran-genie Package on Kali Linux

Last updated: May 11,2024

1. Install "r-cran-genie" package

Learn how to install r-cran-genie on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-genie
            
                    
    
    Copied

2. Uninstall "r-cran-genie" package

This guide let you learn how to uninstall r-cran-genie on Kali Linux:


    
        
            $
        

        
            
                sudo apt remove
            
                        
                r-cran-genie
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-cran-genie package on Kali Linux

Package: r-cran-genie
Version: 1.0.5-2
Installed-Size: 295
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-base-core (>= 4.0.3-1), r-api-4.0, r-cran-genieclust, r-cran-rcpp (>= 1.0.0), libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 6), libstdc++6 (>= 5.2)
Recommends: r-cran-testthat
Suggests: r-cran-stringi
Size: 93320
SHA256: 4ccb0b05a52612eebc0c32ee8aeeeaedce4cfd10f2936d3ac3d175ad5a7eadea
SHA1: 230d1cb5e9d3818d2d71162869c179957cb9f94f
MD5sum: 1ee80977b50c882d346b4310a98dba53
Description: GNU R fast, robust, and outlier resistant hierarchical clustering
Includes the reference implementation of Genie - a hierarchical
clustering algorithm that links two point groups in such a way that
an inequity measure (namely, the Gini index) of the cluster sizes
does not significantly increase above a given threshold.
This method most often outperforms many other data segmentation approaches
in terms of clustering quality as tested on a wide range of benchmark
datasets. At the same time, Genie retains the high speed of the single
linkage approach, therefore it is also suitable for analysing larger data sets.
For more details see (Gagolewski et al. 2016 ).
For an even faster and more feature-rich implementation, including,
amongst others, noise point detection, see the 'genieclust' package.
Description-md5:
Homepage: https://cran.r-project.org/package=genie
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-genie/r-cran-genie_1.0.5-2_amd64.deb