NLP.Concraft.Disamb.Tiered

Tiered model

newtype Ob

Observation.

Constructors

Ob

Fields

unOb :: Int

Instances

Eq Ob

Ord Ob

Show Ob

Ix Ob

Binary Ob

newtype Lb

Sub

label.

Constructors

Lb

Fields

unLb :: Int

Instances

Eq Lb

Ord Lb

Show Lb

Ix Lb

Binary Lb

data Feat

Feature.

Constructors

TFeat3

Fields

x1 :: !Lb

x2 :: !Lb

x3 :: !Lb

ln :: !Int

TFeat2

Fields

x1 :: !Lb

x2 :: !Lb

ln :: !Int

TFeat1

Fields

x1 :: !Lb

ln :: !Int

OFeat

Fields

ob :: !Ob

x1 :: !Lb

ln :: !Int

Instances

Eq Feat

Ord Feat

Show Feat

Binary Feat

FeatMap FeatMap Feat

Binary (FeatMap Feat)

data CRF a b

CRF model data.

Constructors

CRF

Fields

numOfLayers :: Int

codecData :: CodecData a b

model :: Model FeatMap Ob [Lb] Feat

Instances

(Ord a, Ord b, Binary a, Binary b) => Binary (CRF a b)

train

Arguments

:: (Ord o, Ord t)

=> Int

Number of tagging layers

-> FeatSel Ob [Lb] Feat

Feature selection

-> SgdArgs

Args for SGD

-> TrainCRF o [t] (CRF o t)

Train the CRF using the stochastic gradient descent method. Use the provided feature selection function to determine model features.

tag :: (Ord o, Ord t) => CRF o t -> TagCRF o [t]

Find the most probable label sequence.

Feature selection

type FeatSel o t f = FeatGen o t f -> Xs o t -> Ys t -> [f]

A feature selection function type.

selectHidden :: FeatSel o t f

The hiddenFeats adapted to fit feature selection specs.

selectPresent :: FeatSel o t f

The presentFeats adapted to fit feature selection specs.