Package cc.mallet.fst.semi_supervised
-
Class Summary Class Description CRFOptimizableByEntropyRegularization A CRF objective function that is the entropy of the CRF's predictions on unlabeled data.CRFOptimizableByGE Optimizable for CRF using Generalized Expectation constraints that consider either a single label or a pair of labels of a linear chain CRF.CRFTrainerByEntropyRegularization A CRF trainer that maximizes the log-likelihood plus a weighted entropy regularization term on unlabeled data.CRFTrainerByGE Trains a CRF using Generalized Expectation constraints that consider either a single label or a pair of labels of a linear chain CRF.CRFTrainerByLikelihoodAndGE EntropyLattice Runs subsequence constrained forward-backward to compute the entropy of label sequences.FSTConstraintUtil Expectation constraint utilities for fst package.GELattice Runs the dynamic programming algorithm of [Mann and McCallum 08] for computing the gradient of a Generalized Expectation constraint that considers a single label of a linear chain CRF.StateLabelMap Maps states in the lattice to labels.
DataMelt 3.0 © DataMelt by jWork.ORG