Cabal revisions of crf-chain1-0.2.2
Hackage metadata revisions edit the .cabal file after upload; each diff below is one revision.
revision 1
-name: crf-chain1-version: 0.2.2-synopsis: First-order, linear-chain conditional random fields-description:- 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.-license: BSD3-license-file: LICENSE-cabal-version: >= 1.6-copyright: Copyright (c) 2012 IPI PAN-author: Jakub Waszczuk-maintainer: waszczuk.kuba@gmail.com-stability: experimental-category: Math-homepage: https://github.com/kawu/crf-chain1-build-type: Simple--library- build-depends:- base >= 4 && < 5- , containers- , vector- , array- , random- , parallel- , logfloat- , monad-codec >= 0.2 && < 0.3- , binary- , vector-binary >= 0.1 && < 0.2- , data-lens- , sgd >= 0.2.1 && < 0.3- , vector-th-unbox >= 0.2.1 && < 0.3-- exposed-modules:- Data.CRF.Chain1- , Data.CRF.Chain1.Dataset.Internal- , Data.CRF.Chain1.Dataset.External- , Data.CRF.Chain1.Dataset.Codec- , Data.CRF.Chain1.Feature- , Data.CRF.Chain1.Feature.Present- , Data.CRF.Chain1.Feature.Hidden- , Data.CRF.Chain1.Model- , Data.CRF.Chain1.Inference- , Data.CRF.Chain1.Train-- other-modules:- Data.CRF.Chain1.DP- Data.CRF.Chain1.Util-- ghc-options: -Wall -O2--source-repository head- type: git- location: git://github.com/kawu/crf-chain1.git+name: crf-chain1 +version: 0.2.2 +x-revision: 1 +synopsis: First-order, linear-chain conditional random fields +description: + 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. +license: BSD3 +license-file: LICENSE +cabal-version: >= 1.6 +copyright: Copyright (c) 2012 IPI PAN +author: Jakub Waszczuk +maintainer: waszczuk.kuba@gmail.com +stability: experimental +category: Math +homepage: https://github.com/kawu/crf-chain1 +build-type: Simple + +library + build-depends: + base >= 4 && < 4.8 + , containers + , vector + , array + , random + , parallel + , logfloat + , monad-codec >= 0.2 && < 0.3 + , binary + , vector-binary >= 0.1 && < 0.2 + , data-lens + , sgd >= 0.2.1 && < 0.3 + , vector-th-unbox >= 0.2.1 && < 0.3 + + exposed-modules: + Data.CRF.Chain1 + , Data.CRF.Chain1.Dataset.Internal + , Data.CRF.Chain1.Dataset.External + , Data.CRF.Chain1.Dataset.Codec + , Data.CRF.Chain1.Feature + , Data.CRF.Chain1.Feature.Present + , Data.CRF.Chain1.Feature.Hidden + , Data.CRF.Chain1.Model + , Data.CRF.Chain1.Inference + , Data.CRF.Chain1.Train + + other-modules: + Data.CRF.Chain1.DP + Data.CRF.Chain1.Util + + ghc-options: -Wall -O2 + +source-repository head + type: git + location: git://github.com/kawu/crf-chain1.git