How to Install and Uninstall r-cran-cvst Package on Ubuntu 21.10 (Impish Indri)

Last updated: November 22,2024

1. Install "r-cran-cvst" package

Learn how to install r-cran-cvst on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Please follow the guidelines below to uninstall r-cran-cvst on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                r-cran-cvst
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-cran-cvst package on Ubuntu 21.10 (Impish Indri)

Package: r-cran-cvst
Architecture: all
Version: 0.2-2-3build1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 115
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-kernlab, r-cran-matrix
Filename: pool/universe/r/r-cran-cvst/r-cran-cvst_0.2-2-3build1_all.deb
Size: 86904
MD5sum: d7766b97e27d7a8d3567c30fd4d3cd88
SHA1: fd45862f0d51425ea6008753bacb20978295bd62
SHA256: bde0f32a706fc5d0f0cfe0b7af3fb3106bfad4d588379211f3c2a0b5b78e55e1
SHA512: 5751b92873c2c13f2d8a48574e37c1260e1a679e3a340b4d80b8ef1828c6755d046a0946b562a257787c2460c6ccca0132002b4e15bc0acc32cc0a172595f5d0
Homepage: https://cran.r-project.org/package=CVST
Description-en: GNU R fast cross-validation via sequential testing
This package implements the fast cross-validation via sequential testing
(CVST) procedure. CVST is an improved cross-validation procedure which
uses non-parametric testing coupled with sequential analysis to
determine the best parameter set on linearly increasing subsets of the
data. By eliminating underperforming candidates quickly and keeping
promising candidates as long as possible, the method speeds up the
computation while preserving the capability of a full cross-validation.
Additionally to the CVST the package contains an implementation of the
ordinary k-fold cross-validation with a flexible and powerful set of
helper objects and methods to handle the overall model selection
process. The implementations of the Cochran's Q test with permutations
and the sequential testing framework of Wald are generic and can
therefore also be used in other contexts.
Description-md5: cc5115a6187ec937b4c3c57724f9bf14