How to Install and Uninstall libfann-doc Package on Ubuntu 21.10 (Impish Indri)

Last updated: November 25,2024

1. Install "libfann-doc" package

Please follow the guidance below to install libfann-doc on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                libfann-doc
            
                    
    
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2. Uninstall "libfann-doc" package

Please follow the guidance below to uninstall libfann-doc on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                libfann-doc
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libfann-doc package on Ubuntu 21.10 (Impish Indri)

Package: libfann-doc
Architecture: all
Version: 2.2.0+ds-6
Multi-Arch: foreign
Priority: optional
Section: universe/doc
Source: libfann
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Christian Kastner
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 12886
Recommends: libfann-dev (= 2.2.0+ds-6)
Filename: pool/universe/libf/libfann/libfann-doc_2.2.0+ds-6_all.deb
Size: 1587780
MD5sum: ffd7f5f290271a0488d2de7e5ce38147
SHA1: 218de37cae570ef2db083f2f9573e9a4d955ec1b
SHA256: 6d8cfd3049ee8242c3ed57dab9efd4b7884cc38e68d8e2affdd4b15fc7c9cf75
SHA512: 86469ced81b3be29ee96c62e5c1031d7631fe10634e670bc3d73dccec41d70f36edcacf5a975d0521ae1bb40131d29a3e20f3b04928f794513e3a5fdabdcf733
Homepage: https://leenissen.dk/fann/wp/
Description-en: API documentation for FANN
Fast Artificial Neural Network Library is a free open
source neural network library, which implements multilayer artificial
neural networks in C with support for both fully connected and
sparsely connected networks. Cross-platform execution in both fixed
and floating point are supported. It includes a framework for easy
handling of training data sets. It is easy to use, versatile, well
documented, and fast.
.
This package contains the API documentation in HTML form and some
introductory material in text form.
Description-md5: 5d510503dca8572a264924a75ac6164e