How to Install and Uninstall libxgboost0 Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 20,2024

1. Install "libxgboost0" package

Please follow the guidelines below to install libxgboost0 on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libxgboost0
            
                    
    
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2. Uninstall "libxgboost0" package

Please follow the step by step instructions below to uninstall libxgboost0 on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                libxgboost0
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libxgboost0 package on Ubuntu 21.10 (Impish Indri)

Package: libxgboost0
Architecture: amd64
Version: 1.2.1-1
Priority: optional
Section: universe/libs
Source: xgboost
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Deep Learning Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 3430
Depends: libc6 (>= 2.29), libdmlc0 (>= 0.0~git20200912.bfad207), libgcc-s1 (>= 3.0), libgomp1 (>= 6), librabit0 (>= 0.0~git20200628.74bf00a), libstdc++6 (>= 9)
Filename: pool/universe/x/xgboost/libxgboost0_1.2.1-1_amd64.deb
Size: 997488
MD5sum: 0097afa332bc160dcb293698bc28da63
SHA1: dca7639b8e38704cfcb41e6155c681195df0cccd
SHA256: 65a615d11bca4bba010329fa1e514c7788f821a48e4f057af9f061c673f30bd7
SHA512: 99456eab2196bf6cdcbaf4941375881c16bd658051dcce5bde58774ef5344f093550c5997b5897717a60d017e20f0e338b06d2c83b98231733e222d613091569
Homepage: https://xgboost.ai/
Description-en: Scalable and Flexible Gradient Boosting (Shared lib)
XGBoost is an optimized distributed gradient boosting library designed to be
highly efficient, flexible and portable. It implements machine learning
algorithms under the Gradient Boosting framework. XGBoost provides a parallel
tree boosting (also known as GBDT, GBM) that solve many data science problems
in a fast and accurate way. The same code runs on major distributed environment
(Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of
examples.
Description-md5: f4037992ebf46ea503a3ba4958f16d23