How to Install and Uninstall timbl Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 14,2024

1. Install "timbl" package

Please follow the guidance below to install timbl on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                timbl
            
                    
    
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2. Uninstall "timbl" package

This tutorial shows how to uninstall timbl on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                timbl
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the timbl package on Ubuntu 21.10 (Impish Indri)

Package: timbl
Architecture: amd64
Version: 6.5-3
Priority: optional
Section: universe/science
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 218
Depends: libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2), libticcutils8 (>= 0.24), libtimbl4 (>= 6.5)
Filename: pool/universe/t/timbl/timbl_6.5-3_amd64.deb
Size: 53040
MD5sum: 7a3e31f064aebbfcb3cfa35ef20bbafd
SHA1: bbf5682bae807290878c4fcd06a152525d5cfcd2
SHA256: 9f21173027e9fc14773af12ce6eba278dc341f6cffe5440f14bc4ff29dda47d1
SHA512: bb7fe3f0228018f92fbc631245ac6a64c82cbff74770d0901a536ef0326c0d217d23d5c17f4b4b5aef65345ab3bae9c58d678d125c3205efbc95179238d510a5
Homepage: https://languagemachines.github.io/timbl/
Description-en: Tilburg Memory Based Learner
Memory-Based Learning (MBL) is a machine-learning method applicable to a wide
range of tasks in Natural Language Processing (NLP).
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The Tilburg Memory Based Learner, TiMBL, is a tool for NLP research, and for
many other domains where classification tasks are learned from examples. It
is an efficient implementation of k-nearest neighbor classifier.
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TiMBL's features are:
* Fast, decision-tree-based implementation of k-nearest neighbor
classification;
* Implementations of IB1 and IB2, IGTree, TRIBL, and TRIBL2 algorithms;
* Similarity metrics: Overlap, MVDM, Jeffrey Divergence, Dot product, Cosine;
* Feature weighting metrics: information gain, gain ratio, chi squared,
shared variance;
* Distance weighting metrics: inverse, inverse linear, exponential decay;
* Extensive verbosity options to inspect nearest neighbor sets;
* Server functionality and extensive API;
* Fast leave-one-out testing and internal cross-validation;
* and Handles user-defined example weighting.
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TiMBL is a product of the Centre of Language and Speech Technology
(Radboud University, Nijmegen, The Netherlands), the ILK Research Group
(Tilburg University, The Netherlands) and the CLiPS Research Centre
(University of Antwerp, Belgium).
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If you do scientific research in NLP, timbl will likely be of use to you.
Description-md5: 9d22c91f8e87a115cd9936586ba62c0a