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

Last updated: May 20,2024

1. Install "shogun-doc-cn" package

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


    
        
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                sudo apt update
            
                    
    
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            $
        

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

This guide covers the steps necessary to uninstall shogun-doc-cn on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                shogun-doc-cn
            
                    
    
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            $
        

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

Package: shogun-doc-cn
Priority: optional
Section: universe/doc
Installed-Size: 232571
Maintainer: Ubuntu Developers
Original-Maintainer: Soeren Sonnenburg
Architecture: all
Source: shogun
Version: 3.2.0-7.3build4
Recommends: libshogun-dev
Filename: pool/universe/s/shogun/shogun-doc-cn_3.2.0-7.3build4_all.deb
Size: 23460722
MD5sum: 56fc092913f02360625b7af3502180e2
SHA1: 5b00394a2c714685159eff9db26f434dfe6a2076
SHA256: b0f5ea850dde22655b6adb9026abde8a9a99bf5c369895cff7cf8067823d8858
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
Chinese user and developer documentation.
Description-md5: 7efd1cc18219e0ce334e65b6e7fed49c
Homepage: http://www.shogun-toolbox.org
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu