How to Install and Uninstall r-cran-gbm Package on Kali Linux
Last updated: December 24,2024
1. Install "r-cran-gbm" package
Please follow the steps below to install r-cran-gbm on Kali Linux
$
sudo apt update
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$
sudo apt install
r-cran-gbm
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2. Uninstall "r-cran-gbm" package
Please follow the steps below to uninstall r-cran-gbm on Kali Linux:
$
sudo apt remove
r-cran-gbm
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the r-cran-gbm package on Kali Linux
Package: r-cran-gbm
Version: 2.1.8.1-1
Installed-Size: 766
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-base-core (>= 4.2.1-2), r-api-4.0, r-cran-lattice, r-cran-survival, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Suggests: r-cran-covr, r-cran-gridextra, r-cran-knitr, r-cran-runit, r-cran-tinytest, r-cran-viridis
Size: 566144
SHA256: 7350860190523c96f08d815f263731f0d07fd7f74eadf4120a9908ef191064ad
SHA1: 1d21b70badb203432606857bf1e2c64134e94175
MD5sum: c7e94df6d3cd0ae997e8a6aa6353db84
Description: GNU R package providing Generalized Boosted Regression Models
This package implements extensions to Freund and Schapire's AdaBoost algorithm
and Friedman's gradient boosting machine. Includes regression methods for least
squares, absolute loss, t-distribution loss, quantile regression, logistic,
multinomial logistic, Poisson, Cox proportional hazards partial likelihood,
AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures
(LambdaMart).
Description-md5:
Homepage: https://cran.r-project.org/package=gbm
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-gbm/r-cran-gbm_2.1.8.1-1_amd64.deb
Version: 2.1.8.1-1
Installed-Size: 766
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-base-core (>= 4.2.1-2), r-api-4.0, r-cran-lattice, r-cran-survival, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Suggests: r-cran-covr, r-cran-gridextra, r-cran-knitr, r-cran-runit, r-cran-tinytest, r-cran-viridis
Size: 566144
SHA256: 7350860190523c96f08d815f263731f0d07fd7f74eadf4120a9908ef191064ad
SHA1: 1d21b70badb203432606857bf1e2c64134e94175
MD5sum: c7e94df6d3cd0ae997e8a6aa6353db84
Description: GNU R package providing Generalized Boosted Regression Models
This package implements extensions to Freund and Schapire's AdaBoost algorithm
and Friedman's gradient boosting machine. Includes regression methods for least
squares, absolute loss, t-distribution loss, quantile regression, logistic,
multinomial logistic, Poisson, Cox proportional hazards partial likelihood,
AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures
(LambdaMart).
Description-md5:
Homepage: https://cran.r-project.org/package=gbm
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-gbm/r-cran-gbm_2.1.8.1-1_amd64.deb