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

Last updated: May 17,2024

1. Install "r-cran-dbscan" package

Please follow the step by step instructions below to install r-cran-dbscan on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-dbscan
            
                    
    
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2. Uninstall "r-cran-dbscan" package

This guide covers the steps necessary to uninstall r-cran-dbscan on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-cran-dbscan
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-dbscan package on Kali Linux

Package: r-cran-dbscan
Version: 1.1-12+ds-1
Installed-Size: 1646
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-cran-rcpp (>= 1.0.0), libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 13.1)
Recommends: r-cran-fpc, r-cran-testthat, r-cran-dendextend, r-cran-igraph, r-cran-knitr, r-cran-rmarkdown
Size: 1094584
SHA256: 243400db75d7a03e857c5bf061ead745162842c4606ccaa72a3b0618ddc74e4f
SHA1: b0ab4a2a682bbc04d9e31e6865990a281deb0263
MD5sum: a6a7d1a2258299a199c438255ab4c23f
Description: Density Based Clustering of Applications with Noise (DBSCAN)
Density Based Clustering of Applications with Noise (DBSCAN) and
Related Algorithms provides a fast reimplementation of several density-
based algorithms of the DBSCAN family for spatial data. Includes
the clustering algorithms DBSCAN (density-based spatial clustering
of applications with noise) and HDBSCAN (hierarchical DBSCAN), the
ordering algorithm OPTICS (ordering points to identify the
clustering structure), and the outlier detection algorithm LOF
(local outlier factor). The implementations use the kd-tree data
structure (from library ANN) for faster k-nearest neighbor search.
An R interface to fast kNN and fixed-radius NN search is also
provided. Hahsler, Piekenbrock and Doran (2019)
.
Description-md5:
Homepage: https://cran.r-project.org/package=dbscan
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-dbscan/r-cran-dbscan_1.1-12+ds-1_amd64.deb