Safe Haskell	None

Data.CRF.Chain2.Pair

Synopsis

Documentation

data CRF a b c Source

Constructors

CRF
Fields codec :: Codec a b c model :: Model Ob Lb Feat

Instances

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

train Source

Arguments

:: (Ord a, Ord b, Ord c)
=> SgdArgs	Args for SGD
-> IO [SentL a (b, c)]	Training data `IO` action
-> Maybe (IO [SentL a (b, c)])	Maybe evalation data
-> IO (CRF a b c)	Resulting codec and model

Train the CRF using the stochastic gradient descent method. When the evaluation data IO action is Just, the iterative training process will notify the user about the current accuracy on the evaluation part every full iteration over the training part. TODO: Add custom feature extraction function.

tag :: (Ord a, Ord b, Ord c) => CRF a b c -> Sent a (b, c) -> [(b, c)]Source

Find the most probable label sequence.