How to Install and Uninstall liblinear-tools Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: November 22,2024

1. Install "liblinear-tools" package

Please follow the steps below to install liblinear-tools on Ubuntu 21.04 (Hirsute Hippo)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                liblinear-tools
            
                    
    
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2. Uninstall "liblinear-tools" package

Learn how to uninstall liblinear-tools on Ubuntu 21.04 (Hirsute Hippo):


    
        
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                sudo apt remove
            
                        
                liblinear-tools
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the liblinear-tools package on Ubuntu 21.04 (Hirsute Hippo)

Package: liblinear-tools
Architecture: amd64
Version: 2.3.0+dfsg-5
Multi-Arch: foreign
Priority: optional
Section: universe/science
Source: liblinear
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 92
Depends: libc6 (>= 2.4), liblinear4 (= 2.3.0+dfsg-5)
Suggests: libsvm-tools
Filename: pool/universe/libl/liblinear/liblinear-tools_2.3.0+dfsg-5_amd64.deb
Size: 18352
MD5sum: 0ed154b05f931a26db8a2c58fcbe2970
SHA1: 7000d2df9f8b935f96570d7307315d84120b29d0
SHA256: 0ca774ec11bdc342c7bd23e57d4e2e4e88b11737bc537586247d289507dddf8e
SHA512: 23bb885b9e63796c129749a5f8f89dff706821d221306dabddd5bb1432c44ad52723b48ddb69c3165be0cea62ab97783bbd0136e450c1db1ef35280939c5de6c
Homepage: https://www.csie.ntu.edu.tw/~cjlin/liblinear/
Description-en: Standalone applications for LIBLINEAR
LIBLINEAR is a library for learning linear classifiers for large scale
applications. It supports Support Vector Machines (SVM) with L2 and L1
loss, logistic regression, multi class classification and also Linear
Programming Machines (L1-regularized SVMs). Its computational complexity
scales linearly with the number of training examples making it one of
the fastest SVM solvers around. It also provides Python bindings.
.
This package contains the standalone applications.
Description-md5: 9f200c7831938a7e2fa45f605ff3452a