timbl 6.4.13-1build1 source package in Ubuntu
Changelog
timbl (6.4.13-1build1) focal; urgency=medium * No-change rebuild for libgcc-s1 package name change. -- Matthias Klose <email address hidden> Sun, 22 Mar 2020 16:59:44 +0100
Upload details
- Uploaded by:
- Matthias Klose
- Uploaded to:
- Focal
- Original maintainer:
- Debian Science Team
- Architectures:
- any
- Section:
- science
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Focal | release | universe | science |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
timbl_6.4.13.orig.tar.gz | 565.9 KiB | e1a136e0f58486e1e2855b6ca528877d40d8b1e5de3c599a314ed6951d7c9e4b |
timbl_6.4.13-1build1.debian.tar.xz | 5.3 KiB | 5d0b198dd4f3f33487bf11ac2baeae31476b218f5c9024121cb376ab40c235d3 |
timbl_6.4.13-1build1.dsc | 2.1 KiB | 2685954d92aa24fddd304d0545e46a8671934ceb89d78bb42aee0c028ca2d37f |
Available diffs
- diff from 6.4.13-1 (in Debian) to 6.4.13-1build1 (315 bytes)
Binary packages built by this source
- libtimbl-dev: Tilburg Memory Based Learner - development
The Tilburg Memory Based Learner, TiMBL, is a tool for Natural Language
Processing research, and for many other domains where classification tasks are
learned from examples. It is an efficient implementation of k-nearest neighbor
classifier.
.
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).
.
This package provides the TiMBL header files required to compile C++ programs
that use TiMBL.
- libtimbl4: No summary available for libtimbl4 in ubuntu groovy.
No description available for libtimbl4 in ubuntu groovy.
- libtimbl4-dbgsym: debug symbols for libtimbl4
- timbl: 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).
.
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.
.
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.
.
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).
.
If you do scientific research in NLP, timbl will likely be of use to you.
- timbl-dbgsym: debug symbols for timbl