crf-chain1-0.2.2: crf-chain1.cabal

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