The crf-chain1 package
The library provides efficient implementation of the first-order, linear-chain conditional random fields (CRFs).
Important feature of the implemented flavour of CRFs is that transition features which are not included in the CRF model are considered to have probability of 0. It is particularly useful when the training material determines the set of possible label transitions (e.g. when using the IOB encoding method). Furthermore, this design decision makes the implementation much faster for sparse datasets.
|Versions||0.2.0, 0.2.1, 0.2.2|
|Change log||None available|
|Dependencies||array, base (>=4 && <4.8), binary, containers, data-lens, logfloat, monad-codec (==0.2.*), parallel, random, sgd (>=0.2.1 && <0.3), vector, vector-binary (==0.1.*), vector-th-unbox (>=0.2.1 && <0.3) [details]|
|Copyright||Copyright (c) 2012 IPI PAN|
|Source repository||head: git clone git://github.com/kawu/crf-chain1.git|
|Uploaded||Thu Jun 19 10:28:06 UTC 2014 by JakubWaszczuk|
|Updated||Fri Oct 2 13:56:25 UTC 2015 by AdamBergmark to revision 1|
|Downloads||705 total (23 in last 30 days)|
|Status||Docs available [build log]|
Successful builds reported [all 1 reports]
- crf-chain1-0.2.2.tar.gz [browse] (Cabal source package)
- Package description (included in the package)
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