How to Install and Uninstall shogun-cmdline-static Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: June 05,2024

1. Install "shogun-cmdline-static" package

Here is a brief guide to show you how to install shogun-cmdline-static on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                shogun-cmdline-static
            
                    
    
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2. Uninstall "shogun-cmdline-static" package

Please follow the instructions below to uninstall shogun-cmdline-static on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                shogun-cmdline-static
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the shogun-cmdline-static package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: shogun-cmdline-static
Priority: optional
Section: universe/science
Installed-Size: 182
Maintainer: Ubuntu Developers
Original-Maintainer: Soeren Sonnenburg
Architecture: amd64
Source: shogun
Version: 3.2.0-7.3build4
Replaces: shogun-cmdline
Depends: libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libshogun16 (= 3.2.0-7.3build4), libstdc++6 (>= 4.1.1)
Conflicts: shogun-cmdline
Filename: pool/universe/s/shogun/shogun-cmdline-static_3.2.0-7.3build4_amd64.deb
Size: 32744
MD5sum: 24cb0662781949bbb5ef1453f8ccb9d0
SHA1: 998601c1c5d9d44f51e25fa72679d2ad75e93d0c
SHA256: 725293a284b9da6d4b372b2465c05d6ae627b7676735614f1497fc6a8e1033b8
Description-en: Large Scale Machine Learning Toolbox
SHOGUN - is a new machine learning toolbox with focus on large scale kernel
methods and especially on Support Vector Machines (SVM) with focus to
bioinformatics. It provides a generic SVM object interfacing to several
different SVM implementations. Each of the SVMs can be combined with a variety
of the many kernels implemented. It can deal with weighted linear combination
of a number of sub-kernels, each of which not necessarily working on the same
domain, where an optimal sub-kernel weighting can be learned using Multiple
Kernel Learning. Apart from SVM 2-class classification and regression
problems, a number of linear methods like Linear Discriminant Analysis (LDA),
Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to
train hidden markov models are implemented. The input feature-objects can be
dense, sparse or strings and of type int/short/double/char and can be
converted into different feature types. Chains of preprocessors (e.g.
substracting the mean) can be attached to each feature object allowing for
on-the-fly pre-processing.
.
SHOGUN comes in different flavours, a stand-a-lone version and also with
interfaces to Matlab(tm), R, Octave, Readline and Python. This is the Readline
package.
Description-md5: 77514a757d989aed0db98766f5adb36f
Homepage: http://www.shogun-toolbox.org
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu