Uses of Interface
cc.mallet.types.Sequence

Packages that use Sequence

cc.mallet.extract	Unimplemented.
cc.mallet.fst	Transducers, including Conditional Random Fields (CRFs).
cc.mallet.fst.confidence
cc.mallet.fst.semi_supervised.pr
cc.mallet.fst.semi_supervised.tui
cc.mallet.grmm.learning
cc.mallet.pipe.iterator	Classes that generate instances from different kinds of input or data structures.
cc.mallet.types	Fundamental MALLET types, including FeatureVector, Instance, Label etc.
cc.mallet.util	Miscellaneous utilities including command line processing, math functions, lexing, logging.

Uses of Sequence in cc.mallet.extract

Subinterfaces of Sequence in cc.mallet.extract

interface

Tokenization

Classes in cc.mallet.extract that implement Sequence

class	LabeledSpans Created: Oct 31, 2004
class	StringTokenization

Methods in cc.mallet.extract that return Sequence

Sequence	DocumentExtraction.getPredictedLabels()
Sequence	CRFExtractor.pipeInput(java.lang.Object input)

Methods in cc.mallet.extract with parameters of type Sequence

LabeledSpans	TokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq) Converts a the sequence of labels into a set of labeled spans.
LabeledSpans	HierarchicalTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)
LabeledSpans	DefaultTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)
LabeledSpans	ConfidenceTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)
LabeledSpans	BIOTokenizationFilter.constructLabeledSpans(LabelAlphabet dict, java.lang.Object document, Label backgroundTag, Tokenization input, Sequence seq)

Constructors in cc.mallet.extract with parameters of type Sequence

DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background)

DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background)

DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background, TokenizationFilter filter)

DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, Sequence target, java.lang.String background, TokenizationFilter filter)

DocumentExtraction(java.lang.String name, LabelAlphabet dict, Tokenization input, Sequence predicted, java.lang.String background)

Extraction(Extractor extractor, LabelAlphabet dict, java.lang.String name, Tokenization input, Sequence output, java.lang.String background)
Creates an extration given a sequence output by some kind of per-sequece labeler, like an HMM or a CRF.

Uses of Sequence in cc.mallet.fst

Methods in cc.mallet.fst that return Sequence

static Sequence[]	SimpleTagger.apply(Transducer model, Sequence input, int k) Apply a transducer to an input sequence to produce the k highest-scoring output sequences.
Sequence<java.lang.Object>	MaxLatticeDefault.bestOutputSequence()
Sequence<java.lang.Object>	MaxLattice.bestOutputSequence()
Sequence<Transducer.State>	MaxLatticeDefault.bestStateSequence()
Sequence<Transducer.State>	MaxLattice.bestStateSequence()
Sequence	SumLatticeScaling.getInput()
Sequence	SumLatticeDefault.getInput()
Sequence	SumLatticeBeam.getInput()
Sequence	SumLattice.getInput()
Sequence	Segment.getInput()
Sequence	MaxLatticeDefault.getInput()
Sequence	Segment.getPredicted()
Sequence	MaxLatticeDefault.getProvidedOutput()
Sequence	Segment.getSegmentInputSequence()
Sequence	Segment.getTruth()
Sequence[]	CRF.predict(InstanceList testing) Deprecated.
Sequence	Transducer.transduce(Sequence input) Converts the given sequence into another sequence according to this transducer.

Methods in cc.mallet.fst that return types with arguments of type Sequence

java.util.List<Sequence<java.lang.Object>>	MaxLatticeDefault.bestOutputSequences(int n)
java.util.List<Sequence<java.lang.Object>>	MaxLattice.bestOutputSequences(int n)
java.util.List<Sequence<Transducer.State>>	MaxLatticeDefault.bestStateSequences(int n)
java.util.List<Sequence<Transducer.State>>	MaxLattice.bestStateSequences(int n)

Methods in cc.mallet.fst with parameters of type Sequence

static Sequence[]	SimpleTagger.apply(Transducer model, Sequence input, int k) Apply a transducer to an input sequence to produce the k highest-scoring output sequences.
double	MaxLatticeDefault.elementwiseAccuracy(Sequence referenceOutput)
double	MaxLattice.elementwiseAccuracy(Sequence referenceOutput)
MaxLattice	MaxLatticeFactory.newMaxLattice(Transducer trans, Sequence inputSequence)
abstract MaxLattice	MaxLatticeFactory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)
abstract MaxLattice	MaxLatticeFactory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)
MaxLattice	MaxLatticeDefault.Factory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)
MaxLattice	MaxLatticeDefault.Factory.newMaxLattice(Transducer trans, Sequence inputSequence, Sequence outputSequence)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)
SumLattice	SumLatticeScaling.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeScaling.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)
abstract SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet) Returns a SumLattice object to run forward-backward.
abstract SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet) Returns a SumLattice object to run forward-backward.
SumLattice	SumLatticeDefault.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeDefault.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeBeam.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeBeam.Factory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)
SumLattice	SumLatticeFactory.newSumLattice(Transducer trans, Sequence input, Transducer.Incrementor incrementor)
int	MultiSegmentationEvaluator.numIncorrectSegments(Sequence trueOutput, Sequence predOutput) Returns the number of incorrect segments in predOutput
int	MultiSegmentationEvaluator.numIncorrectSegments(Sequence trueOutput, Sequence predOutput) Returns the number of incorrect segments in predOutput
void	Segment.setPredicted(Sequence predicted)
double	MaxLatticeDefault.tokenAccuracy(Sequence referenceOutput, java.io.PrintWriter out)
Sequence	Transducer.transduce(Sequence input) Converts the given sequence into another sequence according to this transducer.
Transducer.TransitionIterator	Transducer.State.transitionIterator(Sequence input, int inputPosition)
Transducer.TransitionIterator	FeatureTransducer.State.transitionIterator(Sequence inputSequence, int inputPosition)
abstract Transducer.TransitionIterator	Transducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)
abstract Transducer.TransitionIterator	Transducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)
Transducer.TransitionIterator	MEMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)
Transducer.TransitionIterator	MEMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)
Transducer.TransitionIterator	HMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)
Transducer.TransitionIterator	HMM.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)
Transducer.TransitionIterator	FeatureTransducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)
Transducer.TransitionIterator	FeatureTransducer.State.transitionIterator(Sequence input, int inputPosition, Sequence output, int outputPosition)
Transducer.TransitionIterator	CRF.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)
Transducer.TransitionIterator	CRF.State.transitionIterator(Sequence inputSequence, int inputPosition, Sequence outputSequence, int outputPosition)

Method parameters in cc.mallet.fst with type arguments of type Sequence

void	MultiSegmentationEvaluator.batchTest(InstanceList data, java.util.List<Sequence> predictedSequences, java.lang.String description, java.io.PrintStream viterbiOutputStream) Tests segmentation using an ArrayList of predicted Sequences instead of a Transducer.

Constructors in cc.mallet.fst with parameters of type Sequence

MaxLatticeDefault(Transducer t, Sequence inputSequence)

MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence)

MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence)

MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence, int maxCaches)
Initiate Viterbi decoding of the inputSequence, contrained to match non-null parts of the outputSequence.

MaxLatticeDefault(Transducer t, Sequence inputSequence, Sequence outputSequence, int maxCaches)
Initiate Viterbi decoding of the inputSequence, contrained to match non-null parts of the outputSequence.

Segment(Sequence input, Sequence pred, Sequence truth, int start, int end, java.lang.Object startTag, java.lang.Object inTag)
Initializes the segment.

Segment(Sequence input, Sequence pred, Sequence truth, int start, int end, java.lang.Object startTag, java.lang.Object inTag)
Initializes the segment.

Segment(Sequence input, Sequence pred, Sequence truth, int start, int end, java.lang.Object startTag, java.lang.Object inTag)
Initializes the segment.

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor)

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor)

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)
Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.

SumLatticeBeam(Transducer t, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)
Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.

SumLatticeConstrained(Transducer t, Sequence input, Sequence output, Segment requiredSegment, Sequence constrainedSequence)

SumLatticeConstrained(Transducer t, Sequence input, Sequence output, Segment requiredSegment, Sequence constrainedSequence)

SumLatticeConstrained(Transducer t, Sequence input, Sequence output, Segment requiredSegment, Sequence constrainedSequence)

SumLatticeConstrained(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)
Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.

SumLatticeConstrained(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, int[] constraints)
Create a lattice that constrains its transitions such that the pairs in "constraints" are adhered to.

SumLatticeDefault(Transducer trans, Sequence input)

SumLatticeDefault(Transducer trans, Sequence input, boolean saveXis)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)

SumLatticeDefault(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)

SumLatticeDefault(Transducer trans, Sequence input, Transducer.Incrementor incrementor)

SumLatticeScaling(Transducer trans, Sequence input)

SumLatticeScaling(Transducer trans, Sequence input, boolean saveXis)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)

SumLatticeScaling(Transducer trans, Sequence input, Sequence output, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet)

SumLatticeScaling(Transducer trans, Sequence input, Transducer.Incrementor incrementor)

Uses of Sequence in cc.mallet.fst.confidence

Constructors in cc.mallet.fst.confidence with parameters of type Sequence

ConfidenceEvaluator.EntityConfidence(double conf, boolean corr, Sequence input, int start, int end)

InstanceWithConfidence(Instance inst, double c, Sequence predicted)

Uses of Sequence in cc.mallet.fst.semi_supervised.pr

Methods in cc.mallet.fst.semi_supervised.pr that return Sequence

Sequence	SumLatticePR.getInput()
Sequence	SumLatticeKL.getInput()
Sequence	SumLatticeDefaultCachedDot.getInput()

Methods in cc.mallet.fst.semi_supervised.pr with parameters of type Sequence

double	PRAuxiliaryModel.getWeight(int index, int position, Sequence input, Transducer.TransitionIterator iter)
void	PRAuxiliaryModel.incrementTransition(int index, int position, Sequence input, Transducer.TransitionIterator iter, double prob)
void	PRAuxiliaryModel.preProcess(int index, int position, Sequence input)

Constructors in cc.mallet.fst.semi_supervised.pr with parameters of type Sequence

CachedDotTransitionIterator(CRF.State source, Sequence inputSeq, int inputPosition, java.lang.String output, double[] dots)

SumLatticeDefaultCachedDot(Transducer trans, Sequence input, Sequence output, double[][][] cachedDots, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeDefaultCachedDot(Transducer trans, Sequence input, Sequence output, double[][][] cachedDots, Transducer.Incrementor incrementor, boolean saveXis, LabelAlphabet outputAlphabet)

SumLatticeKL(Transducer trans, Sequence input, double[] initProbs, double[] finalProbs, double[][][] xis, double[][][] cachedDots, Transducer.Incrementor incrementor)

SumLatticePR(Transducer trans, int index, Sequence input, Sequence output, PRAuxiliaryModel auxModel, double[][][] cachedDots, boolean incrementConstraints, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, boolean saveXis)

SumLatticePR(Transducer trans, int index, Sequence input, Sequence output, PRAuxiliaryModel auxModel, double[][][] cachedDots, boolean incrementConstraints, Transducer.Incrementor incrementor, LabelAlphabet outputAlphabet, boolean saveXis)

Uses of Sequence in cc.mallet.fst.semi_supervised.tui

Methods in cc.mallet.fst.semi_supervised.tui that return Sequence

static Sequence[]

SimpleTaggerWithConstraints.apply(Transducer model, Sequence input, int k) Apply a transducer to an input sequence to produce the k highest-scoring output sequences.

Methods in cc.mallet.fst.semi_supervised.tui with parameters of type Sequence

static Sequence[]

SimpleTaggerWithConstraints.apply(Transducer model, Sequence input, int k) Apply a transducer to an input sequence to produce the k highest-scoring output sequences.

Uses of Sequence in cc.mallet.grmm.learning

Methods in cc.mallet.grmm.learning with parameters of type Sequence

void	MultiSegmentationEvaluatorACRF.TestResults.incrementCounts(Sequence trueOutput, Sequence predOutput)
void	MultiSegmentationEvaluatorACRF.TestResults.incrementCounts(Sequence trueOutput, Sequence predOutput)

Uses of Sequence in cc.mallet.pipe.iterator

Constructors in cc.mallet.pipe.iterator with parameters of type Sequence

SegmentIterator(Instance instance, java.lang.Object[] startTags, java.lang.Object[] inTags, Sequence prediction)
Iterate over segments in one instance.

SegmentIterator(Sequence input, Sequence predicted, Sequence truth, java.lang.Object[] startTags, java.lang.Object[] inTags)
Iterate over segments in one labeled sequence

SegmentIterator(Sequence input, Sequence predicted, Sequence truth, java.lang.Object[] startTags, java.lang.Object[] inTags)
Iterate over segments in one labeled sequence

SegmentIterator(Sequence input, Sequence predicted, Sequence truth, java.lang.Object[] startTags, java.lang.Object[] inTags)
Iterate over segments in one labeled sequence

Uses of Sequence in cc.mallet.types

Classes in cc.mallet.types that implement Sequence

class	ArrayListSequence<E>
class	ArraySequence<E>
class	FeatureSequence An implementation of Sequence that ensures that every Object in the sequence has the same class.
class	FeatureSequenceWithBigrams A FeatureSequence with a parallel record of bigrams, kept in a separate dictionary
class	FeatureVectorSequence
class	LabelSequence
class	LabelsSequence A simple Sequence implementation where all of the elements must be Labels.
class	StringEditFeatureVectorSequence
class	TokenSequence A representation of a piece of text, usually a single word, to which we can attach properties.

Fields in cc.mallet.types declared as Sequence

protected Sequence<I>	SequencePair.input
protected Sequence<O>	SequencePair.output

Methods in cc.mallet.types that return Sequence

Sequence<I>	SequencePair.input()
Sequence<O>	SequencePair.output()

Constructors in cc.mallet.types with parameters of type Sequence

ArraySequence(Sequence<E> s, boolean copy)

SequencePair(Sequence<I> input, Sequence<O> output)

SequencePair(Sequence<I> input, Sequence<O> output)

SequencePairAlignment(Sequence<I> input, Sequence<O> output, double weight)

SequencePairAlignment(Sequence<I> input, Sequence<O> output, double weight)

Uses of Sequence in cc.mallet.util

Methods in cc.mallet.util with parameters of type Sequence

static double	Sequences.elementwiseAccuracy(Sequence truth, Sequence predicted)
static double	Sequences.elementwiseAccuracy(Sequence truth, Sequence predicted)