Uses of Package
cc.mallet.fst

Packages that use cc.mallet.fst

cc.mallet.extract	Unimplemented.
cc.mallet.fst	Transducers, including Conditional Random Fields (CRFs).
cc.mallet.fst.confidence
cc.mallet.fst.semi_supervised
cc.mallet.fst.semi_supervised.constraints
cc.mallet.fst.semi_supervised.pr
cc.mallet.fst.semi_supervised.tui
cc.mallet.pipe.iterator	Classes that generate instances from different kinds of input or data structures.

Classes in cc.mallet.fst used by cc.mallet.extract

CRF
Represents a CRF model.

Classes in cc.mallet.fst used by cc.mallet.fst

CacheStaleIndicator
Indicates when the value/gradient during training becomes stale.

CRF
Represents a CRF model.

CRF.Factors
A simple, transparent container to hold the parameters or sufficient statistics for the CRF.

CRF.State

CRF.TransitionIterator

CRFOptimizableByBatchLabelLikelihood
Implements label likelihood gradient computations for batches of data, can be easily parallelized.

CRFOptimizableByLabelLikelihood
An objective function for CRFs that is the label likelihood plus a Gaussian or hyperbolic prior on parameters.

CRFTrainerByLabelLikelihood
Unlike ClassifierTrainer, TransducerTrainer is not "stateless" between calls to train.

CRFTrainerByValueGradients.OptimizableCRF
An optimizable CRF that contains a collection of objective functions.

FeatureTransducer

FeatureTransducer.State

HMM
A Hidden Markov Model.

HMM.State

MaxLattice
The interface to classes implementing the Viterbi algorithm, finding the best sequence of states for a given input sequence.

MaxLatticeFactory

MEMM
A Maximum Entropy Markov Model.

MEMM.State

MEMMTrainer.MEMMOptimizableByLabelLikelihood
Represents the terms in the objective function.

Segment
Represents a labelled chunk of a Sequence segmented by a Transducer, usually corresponding to some object extracted from an input Sequence.

SegmentationEvaluator

SumLattice
Interface to perform forward-backward during training of a transducer.

SumLatticeDefault
Default, full dynamic programming implementation of the Forward-Backward "Sum-(Product)-Lattice" algorithm

SumLatticeDefault.LatticeNode

SumLatticeFactory
Provides factory methods to create inference engine for training a transducer.

SumLatticeScaling.LatticeNode

Transducer
A base class for all sequence models, analogous to classify.Classifier.

Transducer.Incrementor
Methods to be called by inference methods to indicate partial counts of sufficient statistics.

Transducer.State
An abstract class used to represent the states of the transducer.

Transducer.TransitionIterator
An abstract class to iterate over the states of the transducer.

TransducerEvaluator
An abstract class to evaluate a transducer model.

TransducerTrainer
An abstract class to train and evaluate a transducer model.

TransducerTrainer.ByIncrements

TransducerTrainer.ByInstanceIncrements

TransducerTrainer.ByOptimization

Classes in cc.mallet.fst used by cc.mallet.fst.confidence

Segment
Represents a labelled chunk of a Sequence segmented by a Transducer, usually corresponding to some object extracted from an input Sequence.

SumLatticeDefault
Default, full dynamic programming implementation of the Forward-Backward "Sum-(Product)-Lattice" algorithm

Transducer
A base class for all sequence models, analogous to classify.Classifier.

Classes in cc.mallet.fst used by cc.mallet.fst.semi_supervised

CRF
Represents a CRF model.

CRF.Factors
A simple, transparent container to hold the parameters or sufficient statistics for the CRF.

Transducer
A base class for all sequence models, analogous to classify.Classifier.

Transducer.Incrementor
Methods to be called by inference methods to indicate partial counts of sufficient statistics.

Transducer.State
An abstract class used to represent the states of the transducer.

TransducerTrainer
An abstract class to train and evaluate a transducer model.

TransducerTrainer.ByOptimization

Classes in cc.mallet.fst used by cc.mallet.fst.semi_supervised.constraints

SumLattice
Interface to perform forward-backward during training of a transducer.

Classes in cc.mallet.fst used by cc.mallet.fst.semi_supervised.pr

CRF
Represents a CRF model.

CRF.Factors
A simple, transparent container to hold the parameters or sufficient statistics for the CRF.

CRF.State

SumLattice
Interface to perform forward-backward during training of a transducer.

Transducer
A base class for all sequence models, analogous to classify.Classifier.

Transducer.Incrementor
Methods to be called by inference methods to indicate partial counts of sufficient statistics.

Transducer.State
An abstract class used to represent the states of the transducer.

Transducer.TransitionIterator
An abstract class to iterate over the states of the transducer.

TransducerTrainer
An abstract class to train and evaluate a transducer model.

TransducerTrainer.ByOptimization

Classes in cc.mallet.fst used by cc.mallet.fst.semi_supervised.tui

CRF
Represents a CRF model.

Transducer
A base class for all sequence models, analogous to classify.Classifier.

TransducerEvaluator
An abstract class to evaluate a transducer model.

TransducerTrainer
An abstract class to train and evaluate a transducer model.

Classes in cc.mallet.fst used by cc.mallet.pipe.iterator

Segment
Represents a labelled chunk of a Sequence segmented by a Transducer, usually corresponding to some object extracted from an input Sequence.

Transducer
A base class for all sequence models, analogous to classify.Classifier.