Uses of Package
cc.mallet.fst
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Packages that use cc.mallet.fst Package Description 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 Class Description CRF Represents a CRF model. -
Classes in cc.mallet.fst used by cc.mallet.fst Class Description 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 aSequence
segmented by aTransducer
, usually corresponding to some object extracted from an inputSequence
.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" algorithmSumLatticeDefault.LatticeNode SumLatticeFactory Provides factory methods to create inference engine for training a transducer.SumLatticeScaling.LatticeNode Transducer A base class for all sequence models, analogous toclassify.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 Class Description Segment Represents a labelled chunk of aSequence
segmented by aTransducer
, usually corresponding to some object extracted from an inputSequence
.SumLatticeDefault Default, full dynamic programming implementation of the Forward-Backward "Sum-(Product)-Lattice" algorithmTransducer A base class for all sequence models, analogous toclassify.Classifier
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Classes in cc.mallet.fst used by cc.mallet.fst.semi_supervised Class Description 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 toclassify.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 Class Description SumLattice Interface to perform forward-backward during training of a transducer. -
Classes in cc.mallet.fst used by cc.mallet.fst.semi_supervised.pr Class Description 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 toclassify.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 Class Description CRF Represents a CRF model.Transducer A base class for all sequence models, analogous toclassify.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 Class Description Segment Represents a labelled chunk of aSequence
segmented by aTransducer
, usually corresponding to some object extracted from an inputSequence
.Transducer A base class for all sequence models, analogous toclassify.Classifier
.