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.*), binary, containers, data-lens, logfloat, monad-codec (==0.2.*), parallel, random, sgd (>=0.2.1 && <0.3), vector, vector-binary [details]|
|Copyright||Copyright (c) 2012 IPI PAN|
|Source repository||head: git clone git://github.com/kawu/crf-chain1.git|
|Uploaded||Fri Oct 12 13:16:10 UTC 2012 by JakubWaszczuk|
|Downloads||633 total (31 in last 30 days)|
|Status||Docs uploaded by user|
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- crf-chain1-0.2.1.tar.gz [browse] (Cabal source package)
- Package description (included in the package)
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