How to Install and Uninstall python3-xgboost Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 19,2024

1. Install "python3-xgboost" package

Please follow the guidelines below to install python3-xgboost on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-xgboost
            
                    
    
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2. Uninstall "python3-xgboost" package

Here is a brief guide to show you how to uninstall python3-xgboost on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                python3-xgboost
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-xgboost package on Ubuntu 21.10 (Impish Indri)

Package: python3-xgboost
Architecture: amd64
Version: 1.2.1-1
Priority: optional
Section: universe/python
Source: xgboost
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Deep Learning Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 283
Depends: libxgboost0 (= 1.2.1-1), python3-numpy, python3-scipy, python3:any
Filename: pool/universe/x/xgboost/python3-xgboost_1.2.1-1_amd64.deb
Size: 51824
MD5sum: 9049fd0c3a6aa55a0498484ef659a177
SHA1: 4137ce303425e6e69148460c60b671f71f622e3f
SHA256: da333447fd9cae727a8596d92b001722e612c2a8bc204b651cf6a3293c50a60f
SHA512: 72ead156ed7689ad7f7baa912f3bac170868ddfd6d0bc41c6b9daae6155aa052c9d637fc03ff72e1b5d6fb213c8862a305e6669cb8a8533119e0def2d3ef8176
Homepage: https://xgboost.ai/
Description-en: Scalable and Flexible Gradient Boosting (Python3)
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: 41574b2362ef71f3b57c39ca969a330b