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## Uses of Class
cc.mallet.types.FeatureVectorSequence

Packages that use FeatureVectorSequence
cc.mallet.fst | Transducers, including Conditional Random Fields (CRFs).
cc.mallet.fst.semi_supervised |
cc.mallet.grmm.examples |
cc.mallet.grmm.learning |
cc.mallet.grmm.learning.templates |
cc.mallet.types | Fundamental MALLET types, including FeatureVector, Instance, Label etc.

Uses of FeatureVectorSequence in cc.mallet.fst

Constructors in cc.mallet.fst with parameters of type FeatureVectorSequence
`CRF.TransitionIterator(CRF.State source, FeatureVectorSequence inputSeq, int inputPosition, java.lang.String output, CRF crf)`
`MEMM.TransitionIterator(MEMM.State source, FeatureVectorSequence inputSeq, int inputPosition, java.lang.String output, CRF memm)`

Uses of FeatureVectorSequence in cc.mallet.fst.semi_supervised

Methods in cc.mallet.fst.semi_supervised with parameters of type FeatureVectorSequence
`void` | `GELattice.check(double[][] gammas, double[][][] xis, int li, int fi, FeatureVectorSequence fvs)` Verifies the correctness of the lattice computations.
`void` | `CRFOptimizableByGECriteria.computeGradient(FeatureVectorSequence input, double[][] gammas, double[][][] xis)` Fills gradient from a single instance.
`java.util.BitSet` | `GECriteria.getConstraintBitsForInstance(FeatureVectorSequence fvs)` Returns bits for an instance, each bit corresponds to a feature index and is set if the feature is present in the instance.
`double[]` | `GECriteria.getExpectationForInstance(int featureIndex, FeatureVectorSequence fvs, double[][] gammas)` Returns the expectation of a feature in one instance.
`protected int` | `GECriteria.getExpectationForInstance(int featureIndex, FeatureVectorSequence fvs, double[][] gammas, double[] expectation)` Returns the number of times the feature occurred in the sequence (an instance).
`static double` | `GELattice.logValueOfIndicatorFeature(FeatureVectorSequence fvs, int fi, int ip)` Returns indicator value of feature at specified position in logspace.

Constructors in cc.mallet.fst.semi_supervised with parameters of type FeatureVectorSequence
`EntropyLattice(FeatureVectorSequence fvs, double[][] gammas, double[][][] xis, Transducer transducer, Transducer.Incrementor incrementor, double scalingFactor)` Runs constrained forward-backward.
`GELattice(FeatureVectorSequence fvs, double[][] gammas, double[][][] xis, Transducer transducer, Transducer.Incrementor incrementor, GECriteria geCriteria, boolean check)`

Uses of FeatureVectorSequence in cc.mallet.grmm.examples

Methods in cc.mallet.grmm.examples with parameters of type FeatureVectorSequence
`protected void` | `CrossTemplate1.addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)`

Uses of FeatureVectorSequence in cc.mallet.grmm.learning

Methods in cc.mallet.grmm.learning with parameters of type FeatureVectorSequence
`protected abstract void` | `ACRF.SequenceTemplate.addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)` Adds all instiated cliques for an instance.
`void` | `ACRF.BigramTemplate.addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)`
`void` | `ACRF.UnigramTemplate.addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)`
`void` | `ACRF.PairwiseFactorTemplate.addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)`

Uses of FeatureVectorSequence in cc.mallet.grmm.learning.templates

Methods in cc.mallet.grmm.learning.templates with parameters of type FeatureVectorSequence
`void` | `SimilarTokensTemplate.addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)`

Uses of FeatureVectorSequence in cc.mallet.types

Subclasses of FeatureVectorSequence in cc.mallet.types
`class` | `StringEditFeatureVectorSequence`

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