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

Last updated: June 30,2024

1. Install "shogun-doc-en" package

This is a short guide on how to install shogun-doc-en on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                shogun-doc-en
            
                    
    
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2. Uninstall "shogun-doc-en" package

Please follow the guidance below to uninstall shogun-doc-en on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                shogun-doc-en
            
                    
    
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            $
        

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

Package: shogun-doc-en
Priority: optional
Section: universe/doc
Installed-Size: 233139
Maintainer: Ubuntu Developers
Original-Maintainer: Soeren Sonnenburg
Architecture: all
Source: shogun
Version: 3.2.0-7.3build4
Replaces: shogun-doc
Recommends: libshogun-dev
Conflicts: shogun-doc
Filename: pool/universe/s/shogun/shogun-doc-en_3.2.0-7.3build4_all.deb
Size: 23486710
MD5sum: 148a141b98db12e3fa131db4574643e7
SHA1: 9e49c51b099d61293ce0fd403587994b29c32373
SHA256: 2120cbcec67c7f94f08c21c33680595a53ef301b48ed8c207b962b632bef4982
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 English
user and developer documentation.
Description-md5: 301b3aa7b294b5e8a9c5538100845ced
Homepage: http://www.shogun-toolbox.org
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu